Experiment with Random Difficulty (results based on the bet)
Removing Outliers
## [1] "Outliers : 3qq8dp8jk, 79pn8m6v8, e58u3sinl, hudayxdge, w2x28nknu"
## Empty data.table (0 rows) of 1 col: IDjoueur
## Empty data.table (0 rows) of 1 col: IDjoueur
## Empty data.table (0 rows) of 1 col: IDjoueur
## [1] "Outliers : "## Empty data.table (0 rows) of 1 col: IDjoueur## Empty data.table (0 rows) of 1 col: IDjoueur## Empty data.table (0 rows) of 1 col: IDjoueur
## [1] "Outliers : "## Empty data.table (0 rows) of 1 col: IDjoueur## Empty data.table (0 rows) of 1 col: IDjoueur## Empty data.table (0 rows) of 1 col: IDjoueur## [1] "Total number of outliers: 5"## [1] "Total number of outliers motor task: 1"## [1] "Total number of outliers perceptive task: 1"## [1] "Total number of outliers logical task: 3"Modeling objective difficulty for motor task
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula: perdant ~ difficulty + timeNorm + (1 | IDjoueur)
## Data: DT
##
## AIC BIC logLik deviance df.resid
## 2268.1 2290.2 -1130.0 2260.1 1877
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.9846 -0.7313 0.2308 0.7546 2.8895
##
## Random effects:
## Groups Name Variance Std.Dev.
## IDjoueur (Intercept) 0.5178 0.7196
## Number of obs: 1881, groups: IDjoueur, 57
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -1.1555 0.1548 -7.464 8.42e-14 ***
## difficulty 3.0512 0.2019 15.113 < 2e-16 ***
## timeNorm -0.3871 0.1728 -2.241 0.0251 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) dffclt
## difficulty -0.488
## timeNorm -0.430 -0.167## The result is correct only if all data used by the model has not changed since model was fitted.
## The result is correct only if all data used by the model has not changed since model was fitted.##
## Logique2 Motrice Sensoriel
## 0 1881 0
## [1] "Player levels from ranef:"
## (Intercept)
## Min. :-0.9973563
## 1st Qu.:-0.4243437
## Median :-0.1362009
## Mean :-0.0003041
## 3rd Qu.: 0.3781255
## Max. : 1.6570924
## [1] "Intercept: -1.16 8.4e-14 ***"
## [1] "Difficulty: 3.05 1.3e-51 ***"
## [1] "Time: -0.387 0.025 *"
## [1] "R2 fixed: 0.16"
## [1] "R2 mixed: 0.28"
## [1] "Cross Val: 0.69"
## [1] "AIC: 2300"## 0% 25% 50% 75% 100%
## -1.6570924 -0.3781255 0.1362009 0.4243437 0.9973563
## 0% 25% 50% 75% 100%
## -1.6570924 -0.3781255 0.1362009 0.4243437 0.9973563
## `geom_smooth()` using method = 'gam'
## `geom_smooth()` using method = 'loess'
## `geom_smooth()` using method = 'loess'
## `geom_smooth()` using method = 'loess'
Modeling objective difficulty for sensory task
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula: perdant ~ difficulty + timeNorm + (1 | IDjoueur)
## Data: DT
##
## AIC BIC logLik deviance df.resid
## 1535.4 1557.4 -763.7 1527.4 1811
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -5.2914 -0.4479 0.1164 0.3982 4.7670
##
## Random effects:
## Groups Name Variance Std.Dev.
## IDjoueur (Intercept) 0.5772 0.7598
## Number of obs: 1815, groups: IDjoueur, 55
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -2.2311 0.1826 -12.217 < 2e-16 ***
## difficulty 7.0302 0.3250 21.631 < 2e-16 ***
## timeNorm -1.0832 0.2369 -4.572 4.84e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) dffclt
## difficulty -0.458
## timeNorm -0.385 -0.358## The result is correct only if all data used by the model has not changed since model was fitted.
## The result is correct only if all data used by the model has not changed since model was fitted.##
## Logique2 Motrice Sensoriel
## 0 0 1815
## [1] "Player levels from ranef:"
## (Intercept)
## Min. :-1.527169
## 1st Qu.:-0.388916
## Median :-0.005975
## Mean : 0.002363
## 3rd Qu.: 0.374680
## Max. : 1.350107
## [1] "Intercept: -2.23 2.5e-34 ***"
## [1] "Difficulty: 7.03 9.1e-104 ***"
## [1] "Time: -1.08 4.8e-06 ***"
## [1] "R2 fixed: 0.55"
## [1] "R2 mixed: 0.62"
## [1] "Cross Val: 0.8"
## [1] "AIC: 1500"## 0% 25% 50% 75% 100%
## -1.350106912 -0.374679910 0.005974618 0.388915836 1.527169116
## 0% 25% 50% 75% 100%
## -1.350106912 -0.374679910 0.005974618 0.388915836 1.527169116
## `geom_smooth()` using method = 'gam'
## `geom_smooth()` using method = 'loess'
## `geom_smooth()` using method = 'loess'
## `geom_smooth()` using method = 'loess'
Modeling objective difficulty for logical task
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula: perdant ~ difficulty + timeNorm + (1 | IDjoueur)
## Data: DT
##
## AIC BIC logLik deviance df.resid
## 1816.7 1838.8 -904.3 1808.7 1877
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -5.7618 -0.5239 -0.1972 0.5160 5.0573
##
## Random effects:
## Groups Name Variance Std.Dev.
## IDjoueur (Intercept) 1.067 1.033
## Number of obs: 1881, groups: IDjoueur, 57
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -1.6536 0.1924 -8.596 <2e-16 ***
## difficulty 5.4305 0.2647 20.515 <2e-16 ***
## timeNorm -2.0774 0.2224 -9.340 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) dffclt
## difficulty -0.388
## timeNorm -0.276 -0.437## The result is correct only if all data used by the model has not changed since model was fitted.
## The result is correct only if all data used by the model has not changed since model was fitted.##
## Logique2 Motrice Sensoriel
## 1881 0 0
## [1] "Player levels from ranef:"
## (Intercept)
## Min. :-1.492039
## 1st Qu.:-0.741161
## Median :-0.213560
## Mean : 0.004668
## 3rd Qu.: 0.599760
## Max. : 2.373359
## [1] "Intercept: -1.65 8.2e-18 ***"
## [1] "Difficulty: 5.43 1.6e-93 ***"
## [1] "Time: -2.08 9.6e-21 ***"
## [1] "R2 fixed: 0.38"
## [1] "R2 mixed: 0.53"
## [1] "Cross Val: 0.78"
## [1] "AIC: 1800"## 0% 25% 50% 75% 100%
## -2.3733594 -0.5997602 0.2135598 0.7411607 1.4920388
## 0% 25% 50% 75% 100%
## -2.3733594 -0.5997602 0.2135598 0.7411607 1.4920388
## `geom_smooth()` using method = 'gam'
## `geom_smooth()` using method = 'loess'
## `geom_smooth()` using method = 'loess'
## `geom_smooth()` using method = 'loess'
Influence of Player Profiles
Player profiles
Influence of Player Profiles
Objective level and player profile
Playing video games in general and level for each task
##
## Kendall's rank correlation tau
##
## data: Y and X
## z = 1.0832, p-value = 0.2787
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## 0.1121498
##
## Kendall's rank correlation tau
##
## data: Y and X
## z = -0.27984, p-value = 0.7796
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## -0.02959975
##
## Kendall's rank correlation tau
##
## data: Y and X
## z = -0.18429, p-value = 0.8538
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## -0.01913758Playing board games in general and level for each task
##
## Kendall's rank correlation tau
##
## data: Y and X
## z = 0.92279, p-value = 0.3561
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## 0.09432639
##
## Kendall's rank correlation tau
##
## data: Y and X
## z = -0.40055, p-value = 0.6887
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## -0.04164333
##
## Kendall's rank correlation tau
##
## data: Y and X
## z = -0.83074, p-value = 0.4061
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## -0.08524489Self efficacy and level for each task
## Warning in cor.test.default(Y, X, method = "kendall"): Cannot compute exact
## p-value with ties## Warning: Removed 29 rows containing missing values (geom_point).
##
## Kendall's rank correlation tau
##
## data: Y and X
## z = 0.17852, p-value = 0.8583
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## 0.02429648## Warning in cor.test.default(Y, X, method = "kendall"): Cannot compute exact
## p-value with ties## Warning: Removed 27 rows containing missing values (geom_point).
##
## Kendall's rank correlation tau
##
## data: Y and X
## z = 2.5588, p-value = 0.0105
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## 0.3482495
##
## [1] "self.eff.on.level.s 0.35 0.011 *"## Warning in cor.test.default(Y, X, method = "kendall"): Cannot compute exact
## p-value with ties## Warning: Removed 28 rows containing missing values (geom_point).
##
## Kendall's rank correlation tau
##
## data: Y and X
## z = 0.77294, p-value = 0.4396
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## 0.1034345Risk aversion and level for each task
##
## Kendall's rank correlation tau
##
## data: Y and X
## z = 1.2531, p-value = 0.2102
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## 0.1232133
##
## Kendall's rank correlation tau
##
## data: Y and X
## z = 1.9255, p-value = 0.05417
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## 0.1918732
##
## [1] "risk.av.on.level.s 0.19 0.054 ."
##
## Kendall's rank correlation tau
##
## data: Y and X
## z = 1.0617, p-value = 0.2884
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## 0.1042971Age and level for each task
## Warning: Removed 1 rows containing missing values (geom_point).
##
## Kendall's rank correlation tau
##
## data: Y and X
## z = -1.0129, p-value = 0.3111
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## -0.09643322## Warning: Removed 1 rows containing missing values (geom_point).
##
## Kendall's rank correlation tau
##
## data: Y and X
## z = 2.0949, p-value = 0.03618
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## 0.2036664
##
## [1] "age.on.level.s 0.2 0.036 *"## Warning: Removed 1 rows containing missing values (geom_point).
##
## Kendall's rank correlation tau
##
## data: Y and X
## z = 1.2495, p-value = 0.2115
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## 0.1192254Sex and level for each task
##
## Kendall's rank correlation tau
##
## data: Y and X
## z = -2.3361, p-value = 0.01949
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## -0.257113
##
## [1] "sexe.on.level.m -0.26 0.019 *"
##
## Kendall's rank correlation tau
##
## data: Y and X
## z = 0, p-value = 1
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## 0
##
## Kendall's rank correlation tau
##
## data: Y and X
## z = -0.18884, p-value = 0.8502
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## -0.02078441
##
## Wilcoxon rank sum test
##
## data: B and A
## W = 223, p-value = 0.01897
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
## -0.85282846 -0.09534056
## sample estimates:
## difference in location
## -0.5051082
##
## [1] "sexe.on.level.m.2 -0.51 0.019 * mean(A): 0.16 mean(B): -0.32"
##
## Wilcoxon rank sum test
##
## data: B and A
## W = 333, p-value = 1
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
## -0.3670949 0.4731302
## sample estimates:
## difference in location
## -0.0009246191
##
## Wilcoxon rank sum test
##
## data: B and A
## W = 340, p-value = 0.8583
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
## -0.7335260 0.5047401
## sample estimates:
## difference in location
## -0.02802612Subjective difficulty and play habits
Playing video game in general and subjective difficulty error
##
## Kendall's rank correlation tau
##
## data: Y and X
## z = -0.62185, p-value = 0.534
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## -0.03720939Playing board game in general and subjective difficulty error
##
## Kendall's rank correlation tau
##
## data: Y and X
## z = -3.4464, p-value = 0.0005681
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## -0.2033235
##
## [1] "pbg.on.error -0.2 0.00057 ***"In game level and subjective difficulty error
##
## Kendall's rank correlation tau
##
## data: Y and X
## z = 0.44873, p-value = 0.6536
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## 0.02338143
##
## Kendall's rank correlation tau
##
## data: Y and X
## z = 0.23405, p-value = 0.8149
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## 0.02130326
##
## Kendall's rank correlation tau
##
## data: Y and X
## z = -0.094374, p-value = 0.9248
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## -0.008754209
##
## Kendall's rank correlation tau
##
## data: Y and X
## z = 0.45433, p-value = 0.6496
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## 0.04135338Sex and subjective difficulty error
##
## Kendall's rank correlation tau
##
## data: Y and X
## z = 4.1645, p-value = 3.12e-05
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## 0.2646112
##
## [1] "sexe.on.error 0.26 3.1e-05 ***"
##
## Kendall's rank correlation tau
##
## data: Y and X
## z = 2.3699, p-value = 0.01779
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## 0.2608393
##
## [1] "sexe.on.error.m 0.26 0.018 *"
##
## Kendall's rank correlation tau
##
## data: Y and X
## z = 2.565, p-value = 0.01032
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## 0.2875846
##
## [1] "sexe.on.error.s 0.29 0.01 *"
##
## Kendall's rank correlation tau
##
## data: Y and X
## z = 2.2318, p-value = 0.02563
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## 0.2456339
##
## [1] "sexe.on.error.l 0.25 0.026 *"
##
## Wilcoxon rank sum test with continuity correction
##
## data: B and A
## W = 4376, p-value = 3.143e-05
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
## 0.04977679 0.13237866
## sample estimates:
## difference in location
## 0.09299933
##
## [1] "sexe.on.error.2 0.093 3.1e-05 *** mean(A): -0.093 mean(B): 0.001"
##
## Wilcoxon rank sum test
##
## data: B and A
## W = 501, p-value = 0.01724
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
## 0.01355287 0.15331497
## sample estimates:
## difference in location
## 0.09290042
##
## [1] "sexe.on.error.m.2 0.093 0.017 * mean(A): -0.085 mean(B): 0.0073"
##
## Wilcoxon rank sum test
##
## data: B and A
## W = 476, p-value = 0.009655
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
## 0.02092227 0.15744127
## sample estimates:
## difference in location
## 0.09796631
##
## [1] "sexe.on.error.s.2 0.098 0.0097 ** mean(A): -0.1 mean(B): -0.0014"
##
## Wilcoxon rank sum test
##
## data: B and A
## W = 481, p-value = 0.02523
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
## 0.009389481 0.150561466
## sample estimates:
## difference in location
## 0.09060751
##
## [1] "sexe.on.error.l.2 0.091 0.025 * mean(A): -0.091 mean(B): -0.0033"Risk aversion and subjective difficulty error
##
## Kendall's rank correlation tau
##
## data: Y and X
## z = 0.60676, p-value = 0.544
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## 0.03431688
##
## Kendall's rank correlation tau
##
## data: Y and X
## z = 0.12035, p-value = 0.9042
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## 0.01183404
##
## Kendall's rank correlation tau
##
## data: Y and X
## z = 0.11152, p-value = 0.9112
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## 0.01111235
##
## Kendall's rank correlation tau
##
## data: Y and X
## z = 0.79275, p-value = 0.4279
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## 0.07787518Self efficacy and subjective difficulty error
## Warning: Removed 84 rows containing missing values (geom_point).
##
## Kendall's rank correlation tau
##
## data: Y and X
## z = -2.9644, p-value = 0.003033
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## -0.2277125
##
## [1] "self.eff.on.error -0.23 0.003 **"## Warning in cor.test.default(Y, X, method = "kendall"): Cannot compute exact
## p-value with ties## Warning: Removed 29 rows containing missing values (geom_point).
##
## Kendall's rank correlation tau
##
## data: Y and X
## z = -1.7653, p-value = 0.07751
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## -0.2402652
##
## [1] "self.eff.on.error -0.24 0.078 ."## Warning in cor.test.default(Y, X, method = "kendall"): Cannot compute exact
## p-value with ties## Warning: Removed 27 rows containing missing values (geom_point).
##
## Kendall's rank correlation tau
##
## data: Y and X
## z = -1.6463, p-value = 0.09969
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## -0.2240675
##
## [1] "self.eff.on.error -0.22 0.1 :("## Warning in cor.test.default(Y, X, method = "kendall"): Cannot compute exact
## p-value with ties## Warning: Removed 28 rows containing missing values (geom_point).
##
## Kendall's rank correlation tau
##
## data: Y and X
## z = -1.6401, p-value = 0.101
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## -0.2194829OLD!! We investigate the link between player’s reported game habits, feeling of self efficacy, risk aversion and player’s behavior in the different games. Feeling of self efficacy shows a small link with performance on motor task (Kendal \(\tau\)=0.26, p<0.01) and logical task (Kendal \(\tau\)=0.17, p=0.053). Aversion to risk shows a small link with performance on sensory (Kendal \(\tau\)=0.29, p<0.001) and logical task (Kendal \(\tau\)=0.27 p<0.01). In this experiment, female players tend to have a lower performance on motor (Kendal \(\tau\)=-0.4, p<0.001) and logical tasks (Kendal \(\tau\)=-0.25, p<0.01). Player’s sex is also slightly related to the error between subjective and objective difficulty (Kendal \(\tau\)=-0.19, p=0.053) i.e. compared to male players, female players tend to underestimate logical task difficulty.
Influence of Objective difficulty on Subjective Difficulty
All tasks
## [1] "all"## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties
## obj.diff.bin delta.obj.subj n pval
## 1: 0.03125 0.0096 47 0.64 :(
## 2: 0.09375 0.0440 54 0.052 .
## 3: 0.15625 0.0045 58 0.91 :(
## 4: 0.21875 0.0260 58 0.27 :(
## 5: 0.28125 0.0044 57 0.98 :(
## 6: 0.34375 -0.0400 58 0.25 :(
## 7: 0.40625 -0.0400 58 0.23 :(
## 8: 0.46875 -0.0045 58 0.94 :(
## 9: 0.53125 -0.0190 58 0.54 :(
## 10: 0.59375 -0.0420 58 0.18 :(
## 11: 0.65625 -0.0370 58 0.31 :(
## 12: 0.71875 -0.1100 58 1.9e-05 ***
## 13: 0.78125 -0.1400 58 7.4e-08 ***
## 14: 0.84375 -0.2100 58 1.7e-09 ***
## 15: 0.90625 -0.1900 57 5e-11 ***
## 16: 0.96875 -0.1800 55 1.1e-10 ***
## [1] "mean and sd of nb players per bin"
## nb pval
## 1: 47 0.64 :(
## 2: 54 0.052 .
## 3: 58 0.91 :(
## 4: 58 0.27 :(
## 5: 57 0.98 :(
## 6: 58 0.25 :(
## 7: 58 0.23 :(
## 8: 58 0.94 :(
## 9: 58 0.54 :(
## 10: 58 0.18 :(
## 11: 58 0.31 :(
## 12: 58 1.9e-05 ***
## 13: 58 7.4e-08 ***
## 14: 58 1.7e-09 ***
## 15: 57 5e-11 ***
## 16: 55 1.1e-10 ***
## [1] 56.8
## [1] 2.86
## [1] "good"## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties
## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties
## obj.diff.bin delta.obj.subj n pval
## 1: 0.03125 0.0120 36 0.52 :(
## 2: 0.09375 0.0250 38 0.35 :(
## 3: 0.15625 -0.0310 44 0.22 :(
## 4: 0.21875 -0.0045 42 0.7 :(
## 5: 0.28125 -0.0210 38 0.61 :(
## 6: 0.34375 -0.0580 40 0.37 :(
## 7: 0.40625 -0.0250 38 0.48 :(
## 8: 0.46875 0.0550 39 0.15 :(
## 9: 0.53125 0.0520 41 0.32 :(
## 10: 0.59375 -0.0580 41 0.31 :(
## 11: 0.65625 -0.0490 39 0.21 :(
## 12: 0.71875 -0.1400 39 0.00071 ***
## 13: 0.78125 -0.1400 38 0.00067 ***
## 14: 0.84375 -0.2400 33 6.5e-06 ***
## 15: 0.90625 -0.1900 29 2.5e-06 ***
## 16: 0.96875 -0.1500 19 0.00011 ***
## [1] "mean and sd of nb players per bin"
## nb pval
## 1: 36 0.52 :(
## 2: 38 0.35 :(
## 3: 44 0.22 :(
## 4: 42 0.7 :(
## 5: 38 0.61 :(
## 6: 40 0.37 :(
## 7: 38 0.48 :(
## 8: 39 0.15 :(
## 9: 41 0.32 :(
## 10: 41 0.31 :(
## 11: 39 0.21 :(
## 12: 39 0.00071 ***
## 13: 38 0.00067 ***
## 14: 33 6.5e-06 ***
## 15: 29 2.5e-06 ***
## 16: 19 0.00011 ***
## [1] 37.1
## [1] 5.98
## [1] "medium"## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties
## obj.diff.bin delta.obj.subj n pval
## 1: 0.03125 -0.0310 22 0.026 *
## 2: 0.09375 0.0630 31 0.055 .
## 3: 0.15625 -0.0130 35 0.68 :(
## 4: 0.21875 -0.0044 39 0.94 :(
## 5: 0.28125 -0.0210 40 0.75 :(
## 6: 0.34375 -0.0580 36 0.22 :(
## 7: 0.40625 -0.0630 40 0.37 :(
## 8: 0.46875 -0.0640 40 0.13 :(
## 9: 0.53125 -0.0250 39 0.74 :(
## 10: 0.59375 -0.0220 37 0.55 :(
## 11: 0.65625 0.0012 39 0.95 :(
## 12: 0.71875 -0.0580 39 0.14 :(
## 13: 0.78125 -0.1200 41 0.0018 **
## 14: 0.84375 -0.1400 39 2.8e-05 ***
## 15: 0.90625 -0.1900 32 7.9e-07 ***
## 16: 0.96875 -0.1800 31 1.2e-06 ***
## [1] "mean and sd of nb players per bin"
## nb pval
## 1: 22 0.026 *
## 2: 31 0.055 .
## 3: 35 0.68 :(
## 4: 39 0.94 :(
## 5: 40 0.75 :(
## 6: 36 0.22 :(
## 7: 40 0.37 :(
## 8: 40 0.13 :(
## 9: 39 0.74 :(
## 10: 37 0.55 :(
## 11: 39 0.95 :(
## 12: 39 0.14 :(
## 13: 41 0.0018 **
## 14: 39 2.8e-05 ***
## 15: 32 7.9e-07 ***
## 16: 31 1.2e-06 ***
## [1] 36.2
## [1] 5.04
## [1] "bad"## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties
## obj.diff.bin delta.obj.subj n pval
## 1: 0.03125 NA 0 NA
## 2: 0.09375 NA 6 NA
## 3: 0.15625 0.058 13 0.36 :(
## 4: 0.21875 0.028 15 0.51 :(
## 5: 0.28125 0.140 17 0.28 :(
## 6: 0.34375 0.190 15 0.05 .
## 7: 0.40625 0.022 18 1 :(
## 8: 0.46875 -0.058 17 0.39 :(
## 9: 0.53125 -0.100 14 0.089 .
## 10: 0.59375 -0.110 20 0.21 :(
## 11: 0.65625 -0.085 18 0.21 :(
## 12: 0.71875 -0.190 18 0.0078 **
## 13: 0.78125 -0.110 20 0.013 *
## 14: 0.84375 -0.220 21 0.00026 ***
## 15: 0.90625 -0.130 21 6.2e-05 ***
## 16: 0.96875 -0.250 20 9.6e-05 ***
## [1] "mean and sd of nb players per bin"
## nb pval
## 1: 13 0.36 :(
## 2: 15 0.51 :(
## 3: 17 0.28 :(
## 4: 15 0.05 .
## 5: 18 1 :(
## 6: 17 0.39 :(
## 7: 14 0.089 .
## 8: 20 0.21 :(
## 9: 18 0.21 :(
## 10: 18 0.0078 **
## 11: 20 0.013 *
## 12: 21 0.00026 ***
## 13: 21 6.2e-05 ***
## 14: 20 9.6e-05 ***
## [1] 17.6
## [1] 2.62## Warning: Removed 2 rows containing missing values (geom_point).## Warning: Removed 2 rows containing missing values (geom_errorbar).
Motor task
## [1] "all"## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties
## obj.diff.bin delta.obj.subj n pval
## 1: 0.03125 NA 0 NA
## 2: 0.09375 -0.0940 8 0.71 :(
## 3: 0.15625 -0.0990 29 0.021 *
## 4: 0.21875 -0.0760 41 0.042 *
## 5: 0.28125 -0.0540 48 0.2 :(
## 6: 0.34375 -0.0400 50 0.22 :(
## 7: 0.40625 -0.0015 50 0.9 :(
## 8: 0.46875 -0.0022 54 1 :(
## 9: 0.53125 0.0400 52 0.17 :(
## 10: 0.59375 0.0063 51 0.82 :(
## 11: 0.65625 0.0220 52 0.79 :(
## 12: 0.71875 -0.0580 53 0.064 .
## 13: 0.78125 -0.0790 46 0.015 *
## 14: 0.84375 -0.0940 29 0.077 .
## 15: 0.90625 -0.0760 13 0.0012 **
## 16: 0.96875 -0.1100 6 0.031 *
## [1] "mean and sd of nb players per bin"
## nb pval
## 1: 8 0.71 :(
## 2: 29 0.021 *
## 3: 41 0.042 *
## 4: 48 0.2 :(
## 5: 50 0.22 :(
## 6: 50 0.9 :(
## 7: 54 1 :(
## 8: 52 0.17 :(
## 9: 51 0.82 :(
## 10: 52 0.79 :(
## 11: 53 0.064 .
## 12: 46 0.015 *
## 13: 29 0.077 .
## 14: 13 0.0012 **
## 15: 6 0.031 *
## [1] 38.8
## [1] 17.3## Warning: Removed 1 rows containing missing values (geom_point).## Warning: Removed 1 rows containing missing values (geom_errorbar).
## [1] "good"## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties
## obj.diff.bin delta.obj.subj n pval
## 1: 0.03125 NA 0 NA
## 2: 0.09375 -0.094 8 0.71 :(
## 3: 0.15625 -0.099 24 0.023 *
## 4: 0.21875 -0.066 25 0.067 .
## 5: 0.28125 -0.043 25 0.31 :(
## 6: 0.34375 -0.040 25 0.32 :(
## 7: 0.40625 0.040 24 0.4 :(
## 8: 0.46875 0.067 24 0.12 :(
## 9: 0.53125 0.110 23 0.021 *
## 10: 0.59375 0.120 22 0.043 *
## 11: 0.65625 0.029 22 0.52 :(
## 12: 0.71875 -0.040 21 0.094 .
## 13: 0.78125 -0.067 15 0.32 :(
## 14: 0.84375 NA 2 NA
## 15: 0.90625 NA 0 NA
## 16: 0.96875 NA 0 NA
## [1] "mean and sd of nb players per bin"
## nb pval
## 1: 8 0.71 :(
## 2: 24 0.023 *
## 3: 25 0.067 .
## 4: 25 0.31 :(
## 5: 25 0.32 :(
## 6: 24 0.4 :(
## 7: 24 0.12 :(
## 8: 23 0.021 *
## 9: 22 0.043 *
## 10: 22 0.52 :(
## 11: 21 0.094 .
## 12: 15 0.32 :(
## [1] 21.5
## [1] 5.07## Warning: Removed 4 rows containing missing values (geom_point).## Warning: Removed 4 rows containing missing values (geom_errorbar).
## [1] "medium"## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable
## obj.diff.bin delta.obj.subj n pval
## 1: 0.03125 NA 0 NA
## 2: 0.09375 NA 0 NA
## 3: 0.15625 NA 5 NA
## 4: 0.21875 -0.0045 16 0.41 :(
## 5: 0.28125 -0.0670 23 0.51 :(
## 6: 0.34375 -0.0580 24 0.3 :(
## 7: 0.40625 -0.0320 25 0.73 :(
## 8: 0.46875 -0.0400 25 0.5 :(
## 9: 0.53125 0.0220 25 0.69 :(
## 10: 0.59375 -0.0220 22 0.9 :(
## 11: 0.65625 0.0410 23 0.66 :(
## 12: 0.71875 0.0310 25 0.65 :(
## 13: 0.78125 -0.0670 25 0.13 :(
## 14: 0.84375 -0.0940 20 0.15 :(
## 15: 0.90625 NA 6 NA
## 16: 0.96875 NA 0 NA
## [1] "mean and sd of nb players per bin"
## nb pval
## 1: 16 0.41 :(
## 2: 23 0.51 :(
## 3: 24 0.3 :(
## 4: 25 0.73 :(
## 5: 25 0.5 :(
## 6: 25 0.69 :(
## 7: 22 0.9 :(
## 8: 23 0.66 :(
## 9: 25 0.65 :(
## 10: 25 0.13 :(
## 11: 20 0.15 :(
## [1] 23
## [1] 2.83## Warning: Removed 5 rows containing missing values (geom_point).## Warning: Removed 5 rows containing missing values (geom_errorbar).
## [1] "bad"## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable
## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties
## obj.diff.bin delta.obj.subj n pval
## 1: 0.03125 NA 0 NA
## 2: 0.09375 NA 0 NA
## 3: 0.15625 NA 0 NA
## 4: 0.21875 NA 0 NA
## 5: 0.28125 NA 0 NA
## 6: 0.34375 NA 1 NA
## 7: 0.40625 NA 1 NA
## 8: 0.46875 -0.150 5 0.28 :(
## 9: 0.53125 -0.220 4 0.38 :(
## 10: 0.59375 -0.290 7 0.078 .
## 11: 0.65625 -0.130 7 0.35 :(
## 12: 0.71875 -0.260 7 0.047 *
## 13: 0.78125 -0.160 6 0.16 :(
## 14: 0.84375 -0.120 7 0.2 :(
## 15: 0.90625 -0.081 7 0.022 *
## 16: 0.96875 -0.110 6 0.031 *
## [1] "mean and sd of nb players per bin"
## nb pval
## 1: 5 0.28 :(
## 2: 4 0.38 :(
## 3: 7 0.078 .
## 4: 7 0.35 :(
## 5: 7 0.047 *
## 6: 6 0.16 :(
## 7: 7 0.2 :(
## 8: 7 0.022 *
## 9: 6 0.031 *
## [1] 6.22
## [1] 1.09## Warning: Removed 7 rows containing missing values (geom_point).## Warning: Removed 7 rows containing missing values (geom_errorbar).
Sensory task
## [1] "all"## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties
## obj.diff.bin delta.obj.subj n pval
## 1: 0.03125 -0.0310 32 0.034 *
## 2: 0.09375 -0.0065 48 0.64 :(
## 3: 0.15625 -0.0970 51 0.0069 **
## 4: 0.21875 -0.0760 47 0.0011 **
## 5: 0.28125 -0.0670 46 0.1 :(
## 6: 0.34375 -0.1300 41 0.063 .
## 7: 0.40625 -0.1200 44 0.053 .
## 8: 0.46875 -0.1100 42 0.036 *
## 9: 0.53125 -0.1700 34 0.0079 **
## 10: 0.59375 -0.2400 37 0.00062 ***
## 11: 0.65625 -0.1100 40 0.12 :(
## 12: 0.71875 -0.1700 46 0.00063 ***
## 13: 0.78125 -0.1700 42 0.0042 **
## 14: 0.84375 -0.1700 46 9e-06 ***
## 15: 0.90625 -0.1600 53 1.9e-10 ***
## 16: 0.96875 -0.1400 55 9.4e-11 ***
## [1] "mean and sd of nb players per bin"
## nb pval
## 1: 32 0.034 *
## 2: 48 0.64 :(
## 3: 51 0.0069 **
## 4: 47 0.0011 **
## 5: 46 0.1 :(
## 6: 41 0.063 .
## 7: 44 0.053 .
## 8: 42 0.036 *
## 9: 34 0.0079 **
## 10: 37 0.00062 ***
## 11: 40 0.12 :(
## 12: 46 0.00063 ***
## 13: 42 0.0042 **
## 14: 46 9e-06 ***
## 15: 53 1.9e-10 ***
## 16: 55 9.4e-11 ***
## [1] 44
## [1] 6.4
## [1] "good"## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties
## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties
## obj.diff.bin delta.obj.subj n pval
## 1: 0.03125 0.0044 18 1 :(
## 2: 0.09375 -0.0530 19 0.033 *
## 3: 0.15625 -0.1600 17 0.048 *
## 4: 0.21875 -0.1500 13 0.019 *
## 5: 0.28125 -0.1000 13 0.29 :(
## 6: 0.34375 -0.1300 13 0.024 *
## 7: 0.40625 -0.2600 14 0.008 **
## 8: 0.46875 -0.1100 16 0.22 :(
## 9: 0.53125 -0.2100 14 0.044 *
## 10: 0.59375 -0.4400 11 0.005 **
## 11: 0.65625 -0.1600 13 0.069 .
## 12: 0.71875 -0.1800 16 0.0065 **
## 13: 0.78125 -0.2800 13 0.03 *
## 14: 0.84375 -0.1700 15 0.011 *
## 15: 0.90625 -0.1400 18 0.00018 ***
## 16: 0.96875 -0.1500 19 0.00011 ***
## [1] "mean and sd of nb players per bin"
## nb pval
## 1: 18 1 :(
## 2: 19 0.033 *
## 3: 17 0.048 *
## 4: 13 0.019 *
## 5: 13 0.29 :(
## 6: 13 0.024 *
## 7: 14 0.008 **
## 8: 16 0.22 :(
## 9: 14 0.044 *
## 10: 11 0.005 **
## 11: 13 0.069 .
## 12: 16 0.0065 **
## 13: 13 0.03 *
## 14: 15 0.011 *
## 15: 18 0.00018 ***
## 16: 19 0.00011 ***
## [1] 15.1
## [1] 2.5
## [1] "medium"## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties
## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties
## obj.diff.bin delta.obj.subj n pval
## 1: 0.03125 NA 14 NA
## 2: 0.09375 0.022 25 0.32 :(
## 3: 0.15625 -0.140 25 0.0061 **
## 4: 0.21875 -0.076 24 0.0084 **
## 5: 0.28125 -0.140 23 0.2 :(
## 6: 0.34375 -0.058 20 0.61 :(
## 7: 0.40625 -0.120 21 0.24 :(
## 8: 0.46875 -0.110 20 0.16 :(
## 9: 0.53125 -0.150 16 0.15 :(
## 10: 0.59375 -0.170 20 0.081 .
## 11: 0.65625 -0.160 20 0.49 :(
## 12: 0.71875 -0.110 21 0.013 *
## 13: 0.78125 -0.140 20 0.088 .
## 14: 0.84375 -0.200 23 0.0019 **
## 15: 0.90625 -0.170 25 1.2e-05 ***
## 16: 0.96875 -0.150 26 8.3e-06 ***
## [1] "mean and sd of nb players per bin"
## nb pval
## 1: 25 0.32 :(
## 2: 25 0.0061 **
## 3: 24 0.0084 **
## 4: 23 0.2 :(
## 5: 20 0.61 :(
## 6: 21 0.24 :(
## 7: 20 0.16 :(
## 8: 16 0.15 :(
## 9: 20 0.081 .
## 10: 20 0.49 :(
## 11: 21 0.013 *
## 12: 20 0.088 .
## 13: 23 0.0019 **
## 14: 25 1.2e-05 ***
## 15: 26 8.3e-06 ***
## [1] 21.9
## [1] 2.76## Warning: Removed 1 rows containing missing values (geom_point).## Warning: Removed 1 rows containing missing values (geom_errorbar).
## [1] "bad"## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties
## obj.diff.bin delta.obj.subj n pval
## 1: 0.03125 NA 0 NA
## 2: 0.09375 NA 4 NA
## 3: 0.15625 0.0580 9 0.55 :(
## 4: 0.21875 0.0130 10 1 :(
## 5: 0.28125 0.0044 10 0.92 :(
## 6: 0.34375 -0.0780 8 0.72 :(
## 7: 0.40625 0.0940 9 0.29 :(
## 8: 0.46875 -0.0880 6 0.53 :(
## 9: 0.53125 -0.2300 4 0.36 :(
## 10: 0.59375 -0.1700 6 0.67 :(
## 11: 0.65625 0.0220 7 0.8 :(
## 12: 0.71875 -0.0940 9 0.81 :(
## 13: 0.78125 -0.0670 9 0.48 :(
## 14: 0.84375 -0.0920 8 0.11 :(
## 15: 0.90625 -0.1600 10 0.0056 **
## 16: 0.96875 -0.1200 10 0.0059 **
## [1] "mean and sd of nb players per bin"
## nb pval
## 1: 9 0.55 :(
## 2: 10 1 :(
## 3: 10 0.92 :(
## 4: 8 0.72 :(
## 5: 9 0.29 :(
## 6: 6 0.53 :(
## 7: 4 0.36 :(
## 8: 6 0.67 :(
## 9: 7 0.8 :(
## 10: 9 0.81 :(
## 11: 9 0.48 :(
## 12: 8 0.11 :(
## 13: 10 0.0056 **
## 14: 10 0.0059 **
## [1] 8.21
## [1] 1.85## Warning: Removed 2 rows containing missing values (geom_point).## Warning: Removed 2 rows containing missing values (geom_errorbar).
Logical task
## [1] "all"## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties
## obj.diff.bin delta.obj.subj n pval
## 1: 0.03125 0.0005 38 0.78 :(
## 2: 0.09375 0.0970 43 0.01 *
## 3: 0.15625 0.0940 48 0.04 *
## 4: 0.21875 0.1600 50 0.0046 **
## 5: 0.28125 0.1500 49 0.015 *
## 6: 0.34375 0.0850 41 0.08 .
## 7: 0.40625 0.0220 47 0.77 :(
## 8: 0.46875 -0.0400 47 0.64 :(
## 9: 0.53125 0.0160 45 0.73 :(
## 10: 0.59375 -0.0370 46 0.6 :(
## 11: 0.65625 -0.0490 42 0.32 :(
## 12: 0.71875 -0.1500 41 0.00057 ***
## 13: 0.78125 -0.1400 53 0.00026 ***
## 14: 0.84375 -0.2600 52 1.4e-08 ***
## 15: 0.90625 -0.2400 42 1.7e-08 ***
## 16: 0.96875 -0.3300 29 2.7e-06 ***
## [1] "mean and sd of nb players per bin"
## nb pval
## 1: 38 0.78 :(
## 2: 43 0.01 *
## 3: 48 0.04 *
## 4: 50 0.0046 **
## 5: 49 0.015 *
## 6: 41 0.08 .
## 7: 47 0.77 :(
## 8: 47 0.64 :(
## 9: 45 0.73 :(
## 10: 46 0.6 :(
## 11: 42 0.32 :(
## 12: 41 0.00057 ***
## 13: 53 0.00026 ***
## 14: 52 1.4e-08 ***
## 15: 42 1.7e-08 ***
## 16: 29 2.7e-06 ***
## [1] 44.6
## [1] 5.93
## [1] "good"## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties
## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties
## obj.diff.bin delta.obj.subj n pval
## 1: 0.03125 0.00054 28 0.77 :(
## 2: 0.09375 0.06800 28 0.028 *
## 3: 0.15625 0.05800 27 0.38 :(
## 4: 0.21875 0.15000 25 0.071 .
## 5: 0.28125 0.07100 23 0.44 :(
## 6: 0.34375 0.01300 20 0.9 :(
## 7: 0.40625 0.02200 20 0.72 :(
## 8: 0.46875 0.06700 24 0.43 :(
## 9: 0.53125 0.04000 23 0.61 :(
## 10: 0.59375 -0.12000 22 0.13 :(
## 11: 0.65625 -0.08500 21 0.28 :(
## 12: 0.71875 -0.15000 19 0.016 *
## 13: 0.78125 -0.06700 26 0.14 :(
## 14: 0.84375 -0.27000 24 0.00012 ***
## 15: 0.90625 -0.26000 15 0.00071 ***
## 16: 0.96875 NA 1 NA
## [1] "mean and sd of nb players per bin"
## nb pval
## 1: 28 0.77 :(
## 2: 28 0.028 *
## 3: 27 0.38 :(
## 4: 25 0.071 .
## 5: 23 0.44 :(
## 6: 20 0.9 :(
## 7: 20 0.72 :(
## 8: 24 0.43 :(
## 9: 23 0.61 :(
## 10: 22 0.13 :(
## 11: 21 0.28 :(
## 12: 19 0.016 *
## 13: 26 0.14 :(
## 14: 24 0.00012 ***
## 15: 15 0.00071 ***
## [1] 23
## [1] 3.63## Warning: Removed 1 rows containing missing values (geom_point).## Warning: Removed 1 rows containing missing values (geom_errorbar).
## [1] "medium"## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties
## obj.diff.bin delta.obj.subj n pval
## 1: 0.03125 -0.031 10 1 :(
## 2: 0.09375 0.190 13 0.035 *
## 3: 0.15625 0.190 16 0.046 *
## 4: 0.21875 0.160 16 0.046 *
## 5: 0.28125 0.150 15 0.083 .
## 6: 0.34375 0.085 13 0.44 :(
## 7: 0.40625 0.022 14 0.95 :(
## 8: 0.46875 -0.040 13 0.32 :(
## 9: 0.53125 0.040 12 0.61 :(
## 10: 0.59375 0.120 13 0.57 :(
## 11: 0.65625 -0.049 11 0.5 :(
## 12: 0.71875 -0.150 14 0.23 :(
## 13: 0.78125 -0.270 15 0.0028 **
## 14: 0.84375 -0.160 15 0.0023 **
## 15: 0.90625 -0.250 14 0.0011 **
## 16: 0.96875 -0.330 15 0.00071 ***
## [1] "mean and sd of nb players per bin"
## nb pval
## 1: 10 1 :(
## 2: 13 0.035 *
## 3: 16 0.046 *
## 4: 16 0.046 *
## 5: 15 0.083 .
## 6: 13 0.44 :(
## 7: 14 0.95 :(
## 8: 13 0.32 :(
## 9: 12 0.61 :(
## 10: 13 0.57 :(
## 11: 11 0.5 :(
## 12: 14 0.23 :(
## 13: 15 0.0028 **
## 14: 15 0.0023 **
## 15: 14 0.0011 **
## 16: 15 0.00071 ***
## [1] 13.7
## [1] 1.7
## [1] "bad"## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties
## obj.diff.bin delta.obj.subj n pval
## 1: 0.03125 NA 0 NA
## 2: 0.09375 NA 2 NA
## 3: 0.15625 0.058 5 0.78 :(
## 4: 0.21875 0.210 9 0.4 :(
## 5: 0.28125 0.150 11 0.079 .
## 6: 0.34375 0.400 8 0.041 *
## 7: 0.40625 -0.031 13 0.94 :(
## 8: 0.46875 -0.040 10 0.54 :(
## 9: 0.53125 -0.055 10 0.61 :(
## 10: 0.59375 0.027 11 0.89 :(
## 11: 0.65625 0.110 10 1 :(
## 12: 0.71875 -0.260 8 0.014 *
## 13: 0.78125 -0.075 12 0.12 :(
## 14: 0.84375 -0.270 13 0.0064 **
## 15: 0.90625 -0.140 13 0.0016 **
## 16: 0.96875 -0.340 13 0.00024 ***
## [1] "mean and sd of nb players per bin"
## nb pval
## 1: 5 0.78 :(
## 2: 9 0.4 :(
## 3: 11 0.079 .
## 4: 8 0.041 *
## 5: 13 0.94 :(
## 6: 10 0.54 :(
## 7: 10 0.61 :(
## 8: 11 0.89 :(
## 9: 10 1 :(
## 10: 8 0.014 *
## 11: 12 0.12 :(
## 12: 13 0.0064 **
## 13: 13 0.0016 **
## 14: 13 0.00024 ***
## [1] 10.4
## [1] 2.38## Warning: Removed 2 rows containing missing values (geom_point).## Warning: Removed 2 rows containing missing values (geom_errorbar).
Influence of Playtime on Subjective Difficulty Error
For all groups, motor, sensitive and logical
##
## Call:
## glm(formula = error.subj.diff.mise ~ timeNorm + obj.diff, data = DTM)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.85425 -0.20543 0.02783 0.20243 0.70750
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.006664 0.018685 -0.357 0.721400
## timeNorm 0.016339 0.020930 0.781 0.435103
## obj.diff -0.094710 0.028659 -3.305 0.000969 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for gaussian family taken to be 0.07620175)
##
## Null deviance: 143.99 on 1880 degrees of freedom
## Residual deviance: 143.11 on 1878 degrees of freedom
## AIC: 500.65
##
## Number of Fisher Scoring iterations: 2
##
## Call:
## glm(formula = error.subj.diff.mise ~ timeNorm + obj.diff, data = DTS)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.78155 -0.13780 -0.01151 0.12280 0.83005
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.006795 0.014205 -0.478 0.632
## timeNorm 0.011968 0.020729 0.577 0.564
## obj.diff -0.205459 0.018132 -11.331 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for gaussian family taken to be 0.0706054)
##
## Null deviance: 137.08 on 1814 degrees of freedom
## Residual deviance: 127.94 on 1812 degrees of freedom
## AIC: 344.82
##
## Number of Fisher Scoring iterations: 2
##
## Call:
## glm(formula = error.subj.diff.mise ~ timeNorm + obj.diff, data = DTL)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.71153 -0.24157 0.00719 0.24129 0.65825
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.17431 0.01800 9.684 <2e-16 ***
## timeNorm 0.02107 0.02417 0.872 0.384
## obj.diff -0.46661 0.02329 -20.037 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for gaussian family taken to be 0.1007759)
##
## Null deviance: 230.47 on 1880 degrees of freedom
## Residual deviance: 189.26 on 1878 degrees of freedom
## AIC: 1026.4
##
## Number of Fisher Scoring iterations: 2## time.bin subj.diff.mean obj.diff.mean error.diff n pval
## 1: 1.5 0.3918129 0.4457102 -0.05543814 342 0.0017 **
## 2: 4.5 0.4954052 0.5624859 -0.05783222 171 0.0052 **
## 3: 7.5 0.4928989 0.5357049 -0.03693287 171 0.077 .
## 4: 10.5 0.5071011 0.5362058 -0.02578583 171 0.23 :(
## 5: 13.5 0.4519632 0.5133937 -0.05576376 171 0.0061 **
## 6: 16.5 0.4995823 0.5320036 -0.01539779 171 0.46 :(
## 7: 19.5 0.4803676 0.5358363 -0.04608428 171 0.025 *
## 8: 22.5 0.4527987 0.4961373 -0.03638516 171 0.091 .
## 9: 25.5 0.4536341 0.4868060 -0.02527202 171 0.27 :(
## 10: 28.5 0.4243943 0.4657574 -0.03934980 171 0.074 .
## time error.diff shapes
## 1: 1.5 -0.05543814 24
## 2: 4.5 -0.05783222 24
## 3: 7.5 -0.03693287 16
## 4: 10.5 -0.02578583 16
## 5: 13.5 -0.05576376 24
## 6: 16.5 -0.01539779 16
## 7: 19.5 -0.04608428 24
## 8: 22.5 -0.03638516 16
## 9: 25.5 -0.02527202 16
## 10: 28.5 -0.03934980 16
## time.bin subj.diff.mean obj.diff.mean error.diff n pval
## 1: 1.5 0.2761905 0.3121174 -0.08025653 330 2.2e-05 ***
## 2: 4.5 0.5194805 0.6623901 -0.12246157 165 6.5e-13 ***
## 3: 7.5 0.4259740 0.5756691 -0.12748326 165 6.7e-13 ***
## 4: 10.5 0.4658009 0.6169890 -0.12563962 165 5.6e-14 ***
## 5: 13.5 0.4251082 0.5882784 -0.13475627 165 4.2e-16 ***
## 6: 16.5 0.4025974 0.5480044 -0.12850300 165 1.9e-12 ***
## 7: 19.5 0.4666667 0.5706900 -0.09391859 165 2.3e-08 ***
## 8: 22.5 0.4311688 0.5568448 -0.12173493 165 1.6e-10 ***
## 9: 25.5 0.4891775 0.5635905 -0.08515151 165 7.1e-08 ***
## 10: 28.5 0.4649351 0.5525507 -0.08873994 165 1.2e-07 ***
## time error.diff shapes
## 1: 1.5 -0.08025653 24
## 2: 4.5 -0.12246157 24
## 3: 7.5 -0.12748326 24
## 4: 10.5 -0.12563962 24
## 5: 13.5 -0.13475627 24
## 6: 16.5 -0.12850300 24
## 7: 19.5 -0.09391859 24
## 8: 22.5 -0.12173493 24
## 9: 25.5 -0.08515151 24
## 10: 28.5 -0.08873994 24
## time.bin subj.diff.mean obj.diff.mean error.diff n pval
## 1: 1.5 0.3483709 0.3515160 -0.0257788254 342 0.26 :(
## 2: 4.5 0.5037594 0.6513076 -0.1432600132 171 4.6e-08 ***
## 3: 7.5 0.5037594 0.5682979 -0.0702473202 171 0.0057 **
## 4: 10.5 0.4970760 0.5388474 -0.0530333212 171 0.04 *
## 5: 13.5 0.4761905 0.5225795 -0.0457087630 171 0.099 .
## 6: 16.5 0.4820384 0.5042410 -0.0325739632 171 0.21 :(
## 7: 19.5 0.4185464 0.4415088 -0.0319575055 171 0.25 :(
## 8: 22.5 0.3918129 0.4078173 -0.0213488721 171 0.43 :(
## 9: 25.5 0.3851295 0.3856125 -0.0035008941 171 0.9 :(
## 10: 28.5 0.3792815 0.3513216 -0.0006985616 171 0.98 :(
## time error.diff shapes
## 1: 1.5 -0.0257788254 16
## 2: 4.5 -0.1432600132 24
## 3: 7.5 -0.0702473202 24
## 4: 10.5 -0.0530333212 24
## 5: 13.5 -0.0457087630 16
## 6: 16.5 -0.0325739632 16
## 7: 19.5 -0.0319575055 16
## 8: 22.5 -0.0213488721 16
## 9: 25.5 -0.0035008941 16
## 10: 28.5 -0.0006985616 16
For all taks, per group
##
## Call:
## glm(formula = error.subj.diff.mise ~ timeNorm + obj.diff, data = DTAll[niveau.group ==
## "bad"])
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.7325 -0.2708 0.1282 0.1946 0.5946
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.19395 0.03212 6.039 2.2e-09 ***
## timeNorm 0.02461 0.03362 0.732 0.464
## obj.diff -0.46752 0.03848 -12.150 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for gaussian family taken to be 0.1033257)
##
## Null deviance: 117.24 on 989 degrees of freedom
## Residual deviance: 101.98 on 987 degrees of freedom
## AIC: 567.32
##
## Number of Fisher Scoring iterations: 2
##
## Call:
## glm(formula = error.subj.diff.mise ~ timeNorm + obj.diff, data = DTAll[niveau.group ==
## "medium"])
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.78965 -0.21447 0.05238 0.20809 0.71913
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.06495 0.01608 4.040 5.53e-05 ***
## timeNorm 0.03518 0.02052 1.715 0.0866 .
## obj.diff -0.27531 0.02181 -12.621 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for gaussian family taken to be 0.08591819)
##
## Null deviance: 203.51 on 2210 degrees of freedom
## Residual deviance: 189.71 on 2208 degrees of freedom
## AIC: 852.95
##
## Number of Fisher Scoring iterations: 2
##
## Call:
## glm(formula = error.subj.diff.mise ~ timeNorm + obj.diff, data = DTAll[niveau.group ==
## "good"])
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.74690 -0.18670 -0.07794 0.19292 0.77656
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.05093 0.01314 3.875 0.00011 ***
## timeNorm 0.02188 0.01862 1.175 0.24020
## obj.diff -0.25242 0.02017 -12.515 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for gaussian family taken to be 0.07619937)
##
## Null deviance: 192.86 on 2375 degrees of freedom
## Residual deviance: 180.82 on 2373 degrees of freedom
## AIC: 631.01
##
## Number of Fisher Scoring iterations: 2## time.bin subj.diff.mean obj.diff.mean error.diff n pval
## 1: 1.5 0.4880952 0.5577608 -0.07537700 180 0.011 *
## 2: 4.5 0.6174603 0.7929638 -0.13530294 90 6.4e-07 ***
## 3: 7.5 0.6095238 0.7632260 -0.12467696 90 8.3e-06 ***
## 4: 10.5 0.6063492 0.7231395 -0.10547712 90 0.00047 ***
## 5: 13.5 0.6190476 0.7548209 -0.11446432 90 7e-05 ***
## 6: 16.5 0.5857143 0.7236749 -0.11514344 90 6.8e-05 ***
## 7: 19.5 0.5777778 0.7022849 -0.09756831 90 0.0035 **
## 8: 22.5 0.5904762 0.7080300 -0.09164397 90 0.0023 **
## 9: 25.5 0.5317460 0.6681833 -0.11421844 90 0.00024 ***
## 10: 28.5 0.5888889 0.6369657 -0.04872159 90 0.061 .
## time error.diff shapes
## 1: 1.5 -0.07537700 24
## 2: 4.5 -0.13530294 24
## 3: 7.5 -0.12467696 24
## 4: 10.5 -0.10547712 24
## 5: 13.5 -0.11446432 24
## 6: 16.5 -0.11514344 24
## 7: 19.5 -0.09756831 24
## 8: 22.5 -0.09164397 24
## 9: 25.5 -0.11421844 24
## 10: 28.5 -0.04872159 16
## time.bin subj.diff.mean obj.diff.mean error.diff n pval
## 1: 1.5 0.3511016 0.3849985 -0.04735268 402 0.013 *
## 2: 4.5 0.5508173 0.6963004 -0.12970102 201 4.5e-12 ***
## 3: 7.5 0.4932480 0.5638285 -0.07496709 201 1e-04 ***
## 4: 10.5 0.5238095 0.5926389 -0.07628693 201 0.00051 ***
## 5: 13.5 0.4754797 0.5728047 -0.09734714 201 5.9e-06 ***
## 6: 16.5 0.5031983 0.5659148 -0.06234790 201 0.0062 **
## 7: 19.5 0.5003554 0.5596427 -0.05681502 201 0.0028 **
## 8: 22.5 0.4307036 0.5029846 -0.08285207 201 0.00021 ***
## 9: 25.5 0.4882729 0.5132707 -0.03919351 201 0.087 .
## 10: 28.5 0.4619758 0.5016843 -0.05046452 201 0.012 *
## time error.diff shapes
## 1: 1.5 -0.04735268 24
## 2: 4.5 -0.12970102 24
## 3: 7.5 -0.07496709 24
## 4: 10.5 -0.07628693 24
## 5: 13.5 -0.09734714 24
## 6: 16.5 -0.06234790 24
## 7: 19.5 -0.05681502 24
## 8: 22.5 -0.08285207 24
## 9: 25.5 -0.03919351 16
## 10: 28.5 -0.05046452 24
## time.bin subj.diff.mean obj.diff.mean error.diff n pval
## 1: 1.5 0.2668651 0.2788976 -0.05047545 432 0.002 **
## 2: 4.5 0.4179894 0.4885646 -0.07749843 216 0.00039 ***
## 3: 7.5 0.4014550 0.4710648 -0.07136991 216 0.00047 ***
## 4: 10.5 0.4107143 0.4696033 -0.06239722 216 0.00057 ***
## 5: 13.5 0.3591270 0.4219895 -0.06846433 216 0.00032 ***
## 6: 16.5 0.3723545 0.4108284 -0.04580223 216 0.015 *
## 7: 19.5 0.3617725 0.3962780 -0.04398114 216 0.015 *
## 8: 22.5 0.3511905 0.3779307 -0.03421921 216 0.074 .
## 9: 25.5 0.3617725 0.3651485 -0.01441061 216 0.49 :(
## 10: 28.5 0.3161376 0.3366940 -0.03887147 216 0.036 *
## time error.diff shapes
## 1: 1.5 -0.05047545 24
## 2: 4.5 -0.07749843 24
## 3: 7.5 -0.07136991 24
## 4: 10.5 -0.06239722 24
## 5: 13.5 -0.06846433 24
## 6: 16.5 -0.04580223 24
## 7: 19.5 -0.04398114 24
## 8: 22.5 -0.03421921 16
## 9: 25.5 -0.01441061 16
## 10: 28.5 -0.03887147 24
Per group, motor task
##
## Call:
## glm(formula = error.subj.diff.mise ~ timeNorm + obj.diff, data = DTM[niveau.group ==
## "bad"])
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.78307 -0.20030 0.09965 0.20287 0.56643
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.22999 0.11949 -1.925 0.0555 .
## timeNorm -0.03598 0.06998 -0.514 0.6077
## obj.diff 0.08283 0.15050 0.550 0.5826
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for gaussian family taken to be 0.1038657)
##
## Null deviance: 23.736 on 230 degrees of freedom
## Residual deviance: 23.681 on 228 degrees of freedom
## AIC: 137.39
##
## Number of Fisher Scoring iterations: 2## Warning in wilcox.test.default(subj.diff, obj.diff, conf.int = T, paired =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, obj.diff, conf.int = T, paired =
## T): cannot compute exact confidence interval with ties## time.bin subj.diff.mean obj.diff.mean error.diff n pval
## 1: 1.5 0.5374150 0.7170177 -0.17337940 42 0.011 *
## 2: 4.5 0.6122449 0.7946114 -0.14180958 21 0.0063 **
## 3: 7.5 0.6326531 0.7649789 -0.07966557 21 0.038 *
## 4: 10.5 0.6394558 0.7869246 -0.09982316 21 0.009 **
## 5: 13.5 0.6190476 0.8120284 -0.09702938 21 0.013 *
## 6: 16.5 0.5102041 0.7887369 -0.26023913 21 0.0049 **
## 7: 19.5 0.5442177 0.7250289 -0.16961596 21 0.05 .
## 8: 22.5 0.6462585 0.7637626 -0.03896849 21 0.49 :(
## 9: 25.5 0.5578231 0.8157609 -0.26561302 21 0.00072 ***
## 10: 28.5 0.5986395 0.7674702 -0.09317669 21 0.06 .
## time error.diff shapes
## 1: 1.5 -0.17337940 24
## 2: 4.5 -0.14180958 24
## 3: 7.5 -0.07966557 24
## 4: 10.5 -0.09982316 24
## 5: 13.5 -0.09702938 24
## 6: 16.5 -0.26023913 24
## 7: 19.5 -0.16961596 16
## 8: 22.5 -0.03896849 16
## 9: 25.5 -0.26561302 24
## 10: 28.5 -0.09317669 16## Warning: Removed 2 rows containing missing values (geom_errorbar).
##
## Call:
## glm(formula = error.subj.diff.mise ~ timeNorm + obj.diff, data = DTM[niveau.group ==
## "medium"])
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.79768 -0.22927 0.04496 0.19205 0.68904
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.04646 0.03146 -1.477 0.140
## timeNorm 0.01656 0.03145 0.527 0.599
## obj.diff -0.01154 0.04892 -0.236 0.814
##
## (Dispersion parameter for gaussian family taken to be 0.07542452)
##
## Null deviance: 62.024 on 824 degrees of freedom
## Residual deviance: 61.999 on 822 degrees of freedom
## AIC: 213.93
##
## Number of Fisher Scoring iterations: 2## time.bin subj.diff.mean obj.diff.mean error.diff n pval
## 1: 1.5 0.4219048 0.4703926 -0.04882302 150 0.077 .
## 2: 4.5 0.5314286 0.6181213 -0.07545117 75 0.02 *
## 3: 7.5 0.5028571 0.5405554 -0.02915190 75 0.35 :(
## 4: 10.5 0.5333333 0.5682867 -0.03243828 75 0.34 :(
## 5: 13.5 0.5200000 0.5516441 -0.02674953 75 0.43 :(
## 6: 16.5 0.5428571 0.5685882 -0.02122707 75 0.62 :(
## 7: 19.5 0.5447619 0.5794923 -0.02965771 75 0.39 :(
## 8: 22.5 0.4380952 0.5231952 -0.09195474 75 0.015 *
## 9: 25.5 0.4819048 0.5079792 -0.03043348 75 0.41 :(
## 10: 28.5 0.4819048 0.5148979 -0.03878182 75 0.31 :(
## time error.diff shapes
## 1: 1.5 -0.04882302 16
## 2: 4.5 -0.07545117 24
## 3: 7.5 -0.02915190 16
## 4: 10.5 -0.03243828 16
## 5: 13.5 -0.02674953 16
## 6: 16.5 -0.02122707 16
## 7: 19.5 -0.02965771 16
## 8: 22.5 -0.09195474 24
## 9: 25.5 -0.03043348 16
## 10: 28.5 -0.03878182 16
##
## Call:
## glm(formula = error.subj.diff.mise ~ timeNorm + obj.diff, data = DTM[niveau.group ==
## "good"])
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.80335 -0.18155 -0.01888 0.19399 0.72918
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.06141 0.02493 -2.463 0.0140 *
## timeNorm 0.03220 0.02896 1.112 0.2664
## obj.diff 0.08952 0.04587 1.952 0.0513 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for gaussian family taken to be 0.06387276)
##
## Null deviance: 52.815 on 824 degrees of freedom
## Residual deviance: 52.503 on 822 degrees of freedom
## AIC: 76.782
##
## Number of Fisher Scoring iterations: 2## time.bin subj.diff.mean obj.diff.mean error.diff n pval
## 1: 1.5 0.3209524 0.3450617 -0.03697026 150 0.13 :(
## 2: 4.5 0.4266667 0.4418554 -0.01357897 75 0.61 :(
## 3: 7.5 0.4438095 0.4666577 -0.02092597 75 0.44 :(
## 4: 10.5 0.4438095 0.4339237 0.01170254 75 0.74 :(
## 5: 13.5 0.3371429 0.3915256 -0.05898709 75 0.041 *
## 6: 16.5 0.4533333 0.4235337 0.02549517 75 0.27 :(
## 7: 19.5 0.3980952 0.4392064 -0.03752952 75 0.23 :(
## 8: 22.5 0.4133333 0.3941442 0.01243771 75 0.56 :(
## 9: 25.5 0.3961905 0.3735255 0.02575106 75 0.45 :(
## 10: 28.5 0.3180952 0.3321373 -0.01719639 75 0.56 :(
## time error.diff shapes
## 1: 1.5 -0.03697026 16
## 2: 4.5 -0.01357897 16
## 3: 7.5 -0.02092597 16
## 4: 10.5 0.01170254 16
## 5: 13.5 -0.05898709 24
## 6: 16.5 0.02549517 16
## 7: 19.5 -0.03752952 16
## 8: 22.5 0.01243771 16
## 9: 25.5 0.02575106 16
## 10: 28.5 -0.01719639 16
Per group, sensory task
##
## Call:
## glm(formula = error.subj.diff.mise ~ timeNorm + obj.diff, data = DTS[niveau.group ==
## "bad"])
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.79793 -0.19063 0.05513 0.11328 0.68420
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.12606 0.03963 3.181 0.00161 **
## timeNorm -0.01354 0.05094 -0.266 0.79057
## obj.diff -0.30607 0.04824 -6.345 7.42e-10 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for gaussian family taken to be 0.07755464)
##
## Null deviance: 28.592 on 329 degrees of freedom
## Residual deviance: 25.360 on 327 degrees of freedom
## AIC: 97.751
##
## Number of Fisher Scoring iterations: 2## time.bin subj.diff.mean obj.diff.mean error.diff n pval
## 1: 1.5 0.4404762 0.3993588 0.02189766 60 0.65 :(
## 2: 4.5 0.6666667 0.7366233 -0.08727803 30 0.096 .
## 3: 7.5 0.5809524 0.7568831 -0.13591595 30 0.0017 **
## 4: 10.5 0.5952381 0.7355419 -0.12620101 30 0.013 *
## 5: 13.5 0.6047619 0.7610330 -0.12534868 30 0.00031 ***
## 6: 16.5 0.5571429 0.6560878 -0.11870939 30 0.028 *
## 7: 19.5 0.6000000 0.6794976 -0.09969177 30 0.15 :(
## 8: 22.5 0.6428571 0.7238204 -0.11884304 30 0.033 *
## 9: 25.5 0.4904762 0.6287601 -0.13044938 30 5e-05 ***
## 10: 28.5 0.6095238 0.6027063 -0.02068744 30 0.6 :(
## time error.diff shapes
## 1: 1.5 0.02189766 16
## 2: 4.5 -0.08727803 16
## 3: 7.5 -0.13591595 24
## 4: 10.5 -0.12620101 24
## 5: 13.5 -0.12534868 24
## 6: 16.5 -0.11870939 24
## 7: 19.5 -0.09969177 16
## 8: 22.5 -0.11884304 24
## 9: 25.5 -0.13044938 24
## 10: 28.5 -0.02068744 16
##
## Call:
## glm(formula = error.subj.diff.mise ~ timeNorm + obj.diff, data = DTS[niveau.group ==
## "medium"])
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.78112 -0.13852 0.00505 0.12383 0.79532
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.01377 0.02121 -0.649 0.516
## timeNorm 0.02442 0.03034 0.805 0.421
## obj.diff -0.20178 0.02696 -7.484 1.8e-13 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for gaussian family taken to be 0.07174257)
##
## Null deviance: 65.361 on 857 degrees of freedom
## Residual deviance: 61.340 on 855 degrees of freedom
## AIC: 179.35
##
## Number of Fisher Scoring iterations: 2## time.bin subj.diff.mean obj.diff.mean error.diff n pval
## 1: 1.5 0.2866300 0.3236883 -0.09292927 156 0.01 *
## 2: 4.5 0.5549451 0.7250877 -0.13499915 78 1.9e-08 ***
## 3: 7.5 0.4175824 0.5589565 -0.13125015 78 4.7e-06 ***
## 4: 10.5 0.4633700 0.6300960 -0.13707066 78 2.2e-07 ***
## 5: 13.5 0.4230769 0.6001958 -0.15132217 78 4.6e-09 ***
## 6: 16.5 0.4120879 0.5523362 -0.12659156 78 6.7e-06 ***
## 7: 19.5 0.5054945 0.5853015 -0.08168488 78 0.001 **
## 8: 22.5 0.3864469 0.5177576 -0.13126687 78 4.2e-05 ***
## 9: 25.5 0.5256410 0.5785336 -0.07461127 78 0.00062 ***
## 10: 28.5 0.4835165 0.5789793 -0.09194907 78 2.9e-06 ***
## time error.diff shapes
## 1: 1.5 -0.09292927 24
## 2: 4.5 -0.13499915 24
## 3: 7.5 -0.13125015 24
## 4: 10.5 -0.13707066 24
## 5: 13.5 -0.15132217 24
## 6: 16.5 -0.12659156 24
## 7: 19.5 -0.08168488 24
## 8: 22.5 -0.13126687 24
## 9: 25.5 -0.07461127 24
## 10: 28.5 -0.09194907 24
##
## Call:
## glm(formula = error.subj.diff.mise ~ timeNorm + obj.diff, data = DTS[niveau.group ==
## "good"])
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.6916 -0.1174 -0.0147 0.1402 0.8603
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.03694 0.02141 -1.725 0.085 .
## timeNorm 0.01685 0.03339 0.505 0.614
## obj.diff -0.21183 0.02890 -7.329 7.21e-13 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for gaussian family taken to be 0.06282483)
##
## Null deviance: 42.611 on 626 degrees of freedom
## Residual deviance: 39.203 on 624 degrees of freedom
## AIC: 49.179
##
## Number of Fisher Scoring iterations: 2## time.bin subj.diff.mean obj.diff.mean error.diff n pval
## 1: 1.5 0.1754386 0.2503670 -0.08390482 114 1.7e-07 ***
## 2: 4.5 0.3934837 0.5375232 -0.12642807 57 7.7e-06 ***
## 3: 7.5 0.3558897 0.5031632 -0.10772684 57 7.4e-07 ***
## 4: 10.5 0.4010025 0.5366569 -0.10986449 57 3.5e-07 ***
## 5: 13.5 0.3333333 0.4810470 -0.12968997 57 5.7e-06 ***
## 6: 16.5 0.3082707 0.4851906 -0.14622864 57 1.6e-07 ***
## 7: 19.5 0.3433584 0.4934283 -0.11261380 57 4.9e-06 ***
## 8: 22.5 0.3809524 0.5224507 -0.12657265 57 8.3e-06 ***
## 9: 25.5 0.4385965 0.5088421 -0.07721547 57 0.0098 **
## 10: 28.5 0.3634085 0.4899874 -0.10235022 57 0.00052 ***
## time error.diff shapes
## 1: 1.5 -0.08390482 24
## 2: 4.5 -0.12642807 24
## 3: 7.5 -0.10772684 24
## 4: 10.5 -0.10986449 24
## 5: 13.5 -0.12968997 24
## 6: 16.5 -0.14622864 24
## 7: 19.5 -0.11261380 24
## 8: 22.5 -0.12657265 24
## 9: 25.5 -0.07721547 24
## 10: 28.5 -0.10235022 24
Per group, logical task
##
## Call:
## glm(formula = error.subj.diff.mise ~ timeNorm + obj.diff, data = DTL[niveau.group ==
## "bad"])
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.6715 -0.3210 0.1665 0.2415 0.4398
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.35116 0.05396 6.507 2.15e-10 ***
## timeNorm 0.04197 0.05378 0.780 0.436
## obj.diff -0.70632 0.06280 -11.247 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for gaussian family taken to be 0.1141829)
##
## Null deviance: 63.363 on 428 degrees of freedom
## Residual deviance: 48.642 on 426 degrees of freedom
## AIC: 291.53
##
## Number of Fisher Scoring iterations: 2## time.bin subj.diff.mean obj.diff.mean error.diff n pval
## 1: 1.5 0.4981685 0.5938548 -0.10322431 78 0.037 *
## 2: 4.5 0.5824176 0.8354155 -0.22498741 39 3.5e-05 ***
## 3: 7.5 0.6190476 0.7671613 -0.12052922 39 0.014 *
## 4: 10.5 0.5970696 0.6792534 -0.09030040 39 0.15 :(
## 5: 13.5 0.6300366 0.7192383 -0.10350993 39 0.19 :(
## 6: 16.5 0.6483516 0.7406315 -0.08594203 39 0.051 .
## 7: 19.5 0.5787546 0.7075668 -0.09715808 39 0.11 :(
## 8: 22.5 0.5201465 0.6658736 -0.10308384 39 0.036 *
## 9: 25.5 0.5494505 0.6190439 -0.06832158 39 0.48 :(
## 10: 28.5 0.5677656 0.5930474 -0.03437601 39 0.41 :(
## time error.diff shapes
## 1: 1.5 -0.10322431 24
## 2: 4.5 -0.22498741 24
## 3: 7.5 -0.12052922 24
## 4: 10.5 -0.09030040 16
## 5: 13.5 -0.10350993 16
## 6: 16.5 -0.08594203 16
## 7: 19.5 -0.09715808 16
## 8: 22.5 -0.10308384 24
## 9: 25.5 -0.06832158 16
## 10: 28.5 -0.03437601 16
##
## Call:
## glm(formula = error.subj.diff.mise ~ timeNorm + obj.diff, data = DTL[niveau.group ==
## "medium"])
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.66552 -0.32087 0.07246 0.25616 0.55246
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.25777 0.03707 6.954 1.06e-11 ***
## timeNorm 0.02830 0.04714 0.600 0.549
## obj.diff -0.57891 0.04744 -12.203 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for gaussian family taken to be 0.1074537)
##
## Null deviance: 72.766 on 527 degrees of freedom
## Residual deviance: 56.413 on 525 degrees of freedom
## AIC: 325.58
##
## Number of Fisher Scoring iterations: 2## time.bin subj.diff.mean obj.diff.mean error.diff n pval
## 1: 1.5 0.3452381 0.3511992 0.002063427 96 0.96 :(
## 2: 4.5 0.5744048 0.7716758 -0.199737512 48 1.8e-05 ***
## 3: 7.5 0.6011905 0.6081098 -0.027588261 48 0.59 :(
## 4: 10.5 0.6071429 0.5698214 0.029601910 48 0.65 :(
## 5: 13.5 0.4910714 0.5613575 -0.066831374 48 0.2 :(
## 6: 16.5 0.5892857 0.5838030 -0.001061455 48 0.99 :(
## 7: 19.5 0.4226190 0.4869322 -0.083657414 48 0.17 :(
## 8: 22.5 0.4910714 0.4473991 0.035423984 48 0.57 :(
## 9: 25.5 0.4375000 0.4154865 0.032307242 48 0.64 :(
## 10: 28.5 0.3958333 0.3554335 0.037713301 48 0.62 :(
## time error.diff shapes
## 1: 1.5 0.002063427 16
## 2: 4.5 -0.199737512 24
## 3: 7.5 -0.027588261 16
## 4: 10.5 0.029601910 16
## 5: 13.5 -0.066831374 16
## 6: 16.5 -0.001061455 16
## 7: 19.5 -0.083657414 16
## 8: 22.5 0.035423984 16
## 9: 25.5 0.032307242 16
## 10: 28.5 0.037713301 16
##
## Call:
## glm(formula = error.subj.diff.mise ~ timeNorm + obj.diff, data = DTL[niveau.group ==
## "good"])
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.6749 -0.1924 -0.1188 0.2205 0.7176
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.125918 0.022453 5.608 2.7e-08 ***
## timeNorm 0.003833 0.032082 0.119 0.905
## obj.diff -0.382312 0.034543 -11.068 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for gaussian family taken to be 0.08667836)
##
## Null deviance: 90.633 on 923 degrees of freedom
## Residual deviance: 79.831 on 921 degrees of freedom
## AIC: 367.5
##
## Number of Fisher Scoring iterations: 2## time.bin subj.diff.mean obj.diff.mean error.diff n pval
## 1: 1.5 0.2806122 0.2391825 -0.014248635 168 0.62 :(
## 2: 4.5 0.4268707 0.4970472 -0.076956049 84 0.054 .
## 3: 7.5 0.3945578 0.4532187 -0.067433546 84 0.069 .
## 4: 10.5 0.3877551 0.4559595 -0.061989517 84 0.016 *
## 5: 13.5 0.3962585 0.4091147 -0.010618418 84 0.75 :(
## 6: 16.5 0.3435374 0.3490242 -0.018923182 84 0.57 :(
## 7: 19.5 0.3418367 0.2920256 0.022644031 84 0.57 :(
## 8: 22.5 0.2755102 0.2653873 -0.003699068 84 0.91 :(
## 9: 25.5 0.2789116 0.2601627 -0.008638705 84 0.81 :(
## 10: 28.5 0.2823129 0.2367421 -0.003521999 84 0.95 :(
## time error.diff shapes
## 1: 1.5 -0.014248635 16
## 2: 4.5 -0.076956049 16
## 3: 7.5 -0.067433546 16
## 4: 10.5 -0.061989517 24
## 5: 13.5 -0.010618418 16
## 6: 16.5 -0.018923182 16
## 7: 19.5 0.022644031 16
## 8: 22.5 -0.003699068 16
## 9: 25.5 -0.008638705 16
## 10: 28.5 -0.003521999 16
Link between d(t-1) and error
##
## Call:
## glm(formula = error.subj.diff.mise ~ est.confidence.norm, data = DTM)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.88650 -0.19474 0.02121 0.20015 0.73863
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.02572 0.01258 -2.044 0.0411 *
## est.confidence.norm -0.04321 0.02231 -1.937 0.0529 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for gaussian family taken to be 0.07647613)
##
## Null deviance: 143.99 on 1880 degrees of freedom
## Residual deviance: 143.70 on 1879 degrees of freedom
## AIC: 506.41
##
## Number of Fisher Scoring iterations: 2
##
## Call:
## glm(formula = error.subj.diff.mise ~ est.confidence.norm, data = DTS)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.87482 -0.09574 0.00360 0.07584 0.92532
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.10317 0.01295 -7.968 2.81e-15 ***
## est.confidence.norm -0.01433 0.02181 -0.657 0.511
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for gaussian family taken to be 0.07559423)
##
## Null deviance: 137.08 on 1814 degrees of freedom
## Residual deviance: 137.05 on 1813 degrees of freedom
## AIC: 467.73
##
## Number of Fisher Scoring iterations: 2
##
## Call:
## glm(formula = error.subj.diff.mise ~ est.confidence.norm, data = DTL)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.96055 -0.18551 -0.02757 0.20982 0.87052
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.031481 0.016416 -1.918 0.0553 .
## est.confidence.norm 0.001105 0.028651 0.039 0.9692
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for gaussian family taken to be 0.1226532)
##
## Null deviance: 230.47 on 1880 degrees of freedom
## Residual deviance: 230.47 on 1879 degrees of freedom
## AIC: 1395
##
## Number of Fisher Scoring iterations: 2## Linear mixed model fit by REML t-tests use Satterthwaite approximations
## to degrees of freedom [lmerMod]
## Formula: error.subj.diff.mise ~ est.confidence.norm + (1 | IDjoueur)
## Data: DTAll
##
## REML criterion at convergence: 1633.2
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.7925 -0.5834 -0.0572 0.5586 4.2448
##
## Random effects:
## Groups Name Variance Std.Dev.
## IDjoueur (Intercept) 0.01823 0.1350
## Residual 0.07577 0.2753
## Number of obs: 5577, groups: IDjoueur, 58
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) -0.04362 0.01956 77.00000 -2.230 0.0286 *
## est.confidence.norm -0.03058 0.01486 5560.00000 -2.058 0.0397 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## est.cnfdnc. -0.378
## Linear mixed model fit by REML t-tests use Satterthwaite approximations
## to degrees of freedom [lmerMod]
## Formula: error.subj.diff.mise ~ est.confidence.norm + (1 | IDjoueur)
## Data: DTM
##
## REML criterion at convergence: -162
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.5725 -0.6690 0.0186 0.6541 3.3451
##
## Random effects:
## Groups Name Variance Std.Dev.
## IDjoueur (Intercept) 0.02822 0.1680
## Residual 0.04882 0.2209
## Number of obs: 1881, groups: IDjoueur, 57
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) -0.03875 0.02664 97.80000 -1.455 0.149
## est.confidence.norm -0.01640 0.02826 1731.70000 -0.580 0.562
##
## Correlation of Fixed Effects:
## (Intr)
## est.cnfdnc. -0.516
## Linear mixed model fit by REML t-tests use Satterthwaite approximations
## to degrees of freedom [lmerMod]
## Formula: error.subj.diff.mise ~ est.confidence.norm + (1 | IDjoueur)
## Data: DTS
##
## REML criterion at convergence: 315.7
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.0734 -0.4939 0.0180 0.4206 3.9205
##
## Random effects:
## Groups Name Variance Std.Dev.
## IDjoueur (Intercept) 0.01030 0.1015
## Residual 0.06558 0.2561
## Number of obs: 1815, groups: IDjoueur, 55
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) -0.11702 0.02156 146.20000 -5.428 2.31e-07 ***
## est.confidence.norm 0.01259 0.03019 742.10000 0.417 0.677
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## est.cnfdnc. -0.721
## Linear mixed model fit by REML t-tests use Satterthwaite approximations
## to degrees of freedom [lmerMod]
## Formula: error.subj.diff.mise ~ est.confidence.norm + (1 | IDjoueur)
## Data: DTL
##
## REML criterion at convergence: 998.3
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.5425 -0.6144 -0.0593 0.5775 3.2918
##
## Random effects:
## Groups Name Variance Std.Dev.
## IDjoueur (Intercept) 0.03255 0.1804
## Residual 0.09176 0.3029
## Number of obs: 1881, groups: IDjoueur, 57
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) -0.08898 0.03103 118.30000 -2.867 0.00490 **
## est.confidence.norm 0.11638 0.03715 1557.40000 3.133 0.00176 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## est.cnfdnc. -0.597## Linear mixed model fit by REML t-tests use Satterthwaite approximations
## to degrees of freedom [lmerMod]
## Formula: error.subj.diff.confiance ~ est.confidence.norm + (1 | IDjoueur)
## Data: DTAll
##
## REML criterion at convergence: 1420.5
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.4944 -0.6644 -0.0047 0.6469 4.3628
##
## Random effects:
## Groups Name Variance Std.Dev.
## IDjoueur (Intercept) 0.01073 0.1036
## Residual 0.07329 0.2707
## Number of obs: 5577, groups: IDjoueur, 58
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 3.999e-03 1.583e-02 8.900e+01 0.253 0.801141
## est.confidence.norm -4.890e-02 1.455e-02 5.467e+03 -3.361 0.000782 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## est.cnfdnc. -0.457
## Linear mixed model fit by REML t-tests use Satterthwaite approximations
## to degrees of freedom [lmerMod]
## Formula: error.subj.diff.confiance ~ est.confidence.norm + (1 | IDjoueur)
## Data: DTM
##
## REML criterion at convergence: -691.4
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -4.2105 -0.6953 -0.0188 0.7233 3.1576
##
## Random effects:
## Groups Name Variance Std.Dev.
## IDjoueur (Intercept) 0.02599 0.1612
## Residual 0.03662 0.1914
## Number of obs: 1881, groups: IDjoueur, 57
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) -0.02102 0.02488 90.70000 -0.845 0.400
## est.confidence.norm 0.03031 0.02465 1796.40000 1.229 0.219
##
## Correlation of Fixed Effects:
## (Intr)
## est.cnfdnc. -0.482
## Linear mixed model fit by REML t-tests use Satterthwaite approximations
## to degrees of freedom [lmerMod]
## Formula: error.subj.diff.confiance ~ est.confidence.norm + (1 | IDjoueur)
## Data: DTS
##
## REML criterion at convergence: 577.4
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.0934 -0.6742 0.0414 0.6087 3.9364
##
## Random effects:
## Groups Name Variance Std.Dev.
## IDjoueur (Intercept) 0.01013 0.1006
## Residual 0.07607 0.2758
## Number of obs: 1815, groups: IDjoueur, 55
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) -0.08917 0.02229 146.70000 -4.001 9.97e-05 ***
## est.confidence.norm 0.03712 0.03197 634.90000 1.161 0.246
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## est.cnfdnc. -0.738
## Linear mixed model fit by REML t-tests use Satterthwaite approximations
## to degrees of freedom [lmerMod]
## Formula: error.subj.diff.confiance ~ est.confidence.norm + (1 | IDjoueur)
## Data: DTL
##
## REML criterion at convergence: 832.8
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.9937 -0.7008 -0.0459 0.6928 3.6148
##
## Random effects:
## Groups Name Variance Std.Dev.
## IDjoueur (Intercept) 0.01624 0.1274
## Residual 0.08543 0.2923
## Number of obs: 1881, groups: IDjoueur, 57
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) -0.02690 0.02503 141.90000 -1.075 0.2842
## est.confidence.norm 0.06773 0.03449 1078.00000 1.964 0.0498 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## est.cnfdnc. -0.688All tasks
## [1] "all"## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with zeroes## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with zeroes
## obj.diff.bin delta.obj.subj n pval
## 1: 0.03125 0.150 47 1.8e-05 ***
## 2: 0.09375 0.140 54 5.2e-06 ***
## 3: 0.15625 0.140 58 1.3e-05 ***
## 4: 0.21875 0.100 58 7.1e-05 ***
## 5: 0.28125 0.110 57 1e-05 ***
## 6: 0.34375 0.090 58 0.0014 **
## 7: 0.40625 0.048 58 0.068 .
## 8: 0.46875 0.041 58 0.021 *
## 9: 0.53125 -0.031 58 0.034 *
## 10: 0.59375 -0.052 58 0.018 *
## 11: 0.65625 -0.071 58 0.01 *
## 12: 0.71875 -0.140 58 1.3e-06 ***
## 13: 0.78125 -0.170 58 6.7e-09 ***
## 14: 0.84375 -0.220 58 6.1e-09 ***
## 15: 0.90625 -0.230 57 2.1e-10 ***
## 16: 0.96875 -0.190 55 6.8e-09 ***
## [1] "mean and sd of nb players per bin"
## nb pval
## 1: 47 1.8e-05 ***
## 2: 54 5.2e-06 ***
## 3: 58 1.3e-05 ***
## 4: 58 7.1e-05 ***
## 5: 57 1e-05 ***
## 6: 58 0.0014 **
## 7: 58 0.068 .
## 8: 58 0.021 *
## 9: 58 0.034 *
## 10: 58 0.018 *
## 11: 58 0.01 *
## 12: 58 1.3e-06 ***
## 13: 58 6.7e-09 ***
## 14: 58 6.1e-09 ***
## 15: 57 2.1e-10 ***
## 16: 55 6.8e-09 ***
## [1] 56.8
## [1] 2.86
## [1] "good"## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with zeroes## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with zeroes## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties
## obj.diff.bin delta.obj.subj n pval
## 1: 0.03125 0.1200 36 0.00047 ***
## 2: 0.09375 0.1200 38 0.0018 **
## 3: 0.15625 0.0940 44 0.0071 **
## 4: 0.21875 0.1100 42 0.0029 **
## 5: 0.28125 0.1200 38 0.0017 **
## 6: 0.34375 0.0860 40 0.017 *
## 7: 0.40625 0.0440 38 0.083 .
## 8: 0.46875 0.0480 39 0.039 *
## 9: 0.53125 0.0062 41 0.97 :(
## 10: 0.59375 -0.0770 41 0.16 :(
## 11: 0.65625 -0.0810 39 0.061 .
## 12: 0.71875 -0.1700 39 6.7e-05 ***
## 13: 0.78125 -0.1800 38 5.8e-05 ***
## 14: 0.84375 -0.2700 33 3.5e-06 ***
## 15: 0.90625 -0.2700 29 2.4e-05 ***
## 16: 0.96875 -0.1500 19 0.0027 **
## [1] "mean and sd of nb players per bin"
## nb pval
## 1: 36 0.00047 ***
## 2: 38 0.0018 **
## 3: 44 0.0071 **
## 4: 42 0.0029 **
## 5: 38 0.0017 **
## 6: 40 0.017 *
## 7: 38 0.083 .
## 8: 39 0.039 *
## 9: 41 0.97 :(
## 10: 41 0.16 :(
## 11: 39 0.061 .
## 12: 39 6.7e-05 ***
## 13: 38 5.8e-05 ***
## 14: 33 3.5e-06 ***
## 15: 29 2.4e-05 ***
## 16: 19 0.0027 **
## [1] 37.1
## [1] 5.98
## [1] "medium"## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties
## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties
## obj.diff.bin delta.obj.subj n pval
## 1: 0.03125 0.220 22 0.11 :(
## 2: 0.09375 0.190 31 7.7e-05 ***
## 3: 0.15625 0.110 35 0.0032 **
## 4: 0.21875 0.073 39 0.038 *
## 5: 0.28125 0.120 40 0.011 *
## 6: 0.34375 0.065 36 0.21 :(
## 7: 0.40625 0.022 40 0.77 :(
## 8: 0.46875 0.025 40 0.39 :(
## 9: 0.53125 -0.031 39 0.044 *
## 10: 0.59375 -0.060 37 0.14 :(
## 11: 0.65625 -0.110 39 0.0076 **
## 12: 0.71875 -0.140 39 0.00072 ***
## 13: 0.78125 -0.180 41 1.7e-05 ***
## 14: 0.84375 -0.230 39 1e-06 ***
## 15: 0.90625 -0.220 32 3.2e-06 ***
## 16: 0.96875 -0.170 31 0.00011 ***
## [1] "mean and sd of nb players per bin"
## nb pval
## 1: 22 0.11 :(
## 2: 31 7.7e-05 ***
## 3: 35 0.0032 **
## 4: 39 0.038 *
## 5: 40 0.011 *
## 6: 36 0.21 :(
## 7: 40 0.77 :(
## 8: 40 0.39 :(
## 9: 39 0.044 *
## 10: 37 0.14 :(
## 11: 39 0.0076 **
## 12: 39 0.00072 ***
## 13: 41 1.7e-05 ***
## 14: 39 1e-06 ***
## 15: 32 3.2e-06 ***
## 16: 31 0.00011 ***
## [1] 36.2
## [1] 5.04
## [1] "bad"## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties
## obj.diff.bin delta.obj.subj n pval
## 1: 0.03125 NA 0 NA
## 2: 0.09375 0.160 6 1 :(
## 3: 0.15625 0.260 13 0.011 *
## 4: 0.21875 0.140 15 0.043 *
## 5: 0.28125 0.094 17 0.079 .
## 6: 0.34375 0.260 15 0.0047 **
## 7: 0.40625 0.094 18 0.059 .
## 8: 0.46875 0.056 17 0.45 :(
## 9: 0.53125 -0.031 14 0.083 .
## 10: 0.59375 -0.043 20 0.56 :(
## 11: 0.65625 -0.019 18 1 :(
## 12: 0.71875 -0.200 18 0.005 **
## 13: 0.78125 -0.170 20 0.0029 **
## 14: 0.84375 -0.180 21 0.0017 **
## 15: 0.90625 -0.210 21 0.00025 ***
## 16: 0.96875 -0.330 20 9.3e-05 ***
## [1] "mean and sd of nb players per bin"
## nb pval
## 1: 6 1 :(
## 2: 13 0.011 *
## 3: 15 0.043 *
## 4: 17 0.079 .
## 5: 15 0.0047 **
## 6: 18 0.059 .
## 7: 17 0.45 :(
## 8: 14 0.083 .
## 9: 20 0.56 :(
## 10: 18 1 :(
## 11: 18 0.005 **
## 12: 20 0.0029 **
## 13: 21 0.0017 **
## 14: 21 0.00025 ***
## 15: 20 9.3e-05 ***
## [1] 16.9
## [1] 3.93## Warning: Removed 1 rows containing missing values (geom_point).## Warning: Removed 1 rows containing missing values (geom_errorbar).
Motor task
## [1] "all"## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties
## obj.diff.bin delta.obj.subj n pval
## 1: 0.03125 NA 0 NA
## 2: 0.09375 0.160 8 0.29 :(
## 3: 0.15625 0.094 29 0.22 :(
## 4: 0.21875 0.056 41 0.063 .
## 5: 0.28125 0.085 48 0.01 *
## 6: 0.34375 0.069 50 0.034 *
## 7: 0.40625 0.069 50 0.086 .
## 8: 0.46875 0.044 54 0.03 *
## 9: 0.53125 0.019 52 0.66 :(
## 10: 0.59375 -0.019 51 0.65 :(
## 11: 0.65625 -0.040 52 0.11 :(
## 12: 0.71875 -0.069 53 0.0037 **
## 13: 0.78125 -0.110 46 0.00082 ***
## 14: 0.84375 -0.170 29 0.0015 **
## 15: 0.90625 -0.180 13 0.056 .
## 16: 0.96875 -0.270 6 0.052 .
## [1] "mean and sd of nb players per bin"
## nb pval
## 1: 8 0.29 :(
## 2: 29 0.22 :(
## 3: 41 0.063 .
## 4: 48 0.01 *
## 5: 50 0.034 *
## 6: 50 0.086 .
## 7: 54 0.03 *
## 8: 52 0.66 :(
## 9: 51 0.65 :(
## 10: 52 0.11 :(
## 11: 53 0.0037 **
## 12: 46 0.00082 ***
## 13: 29 0.0015 **
## 14: 13 0.056 .
## 15: 6 0.052 .
## [1] 38.8
## [1] 17.3## Warning: Removed 1 rows containing missing values (geom_point).## Warning: Removed 1 rows containing missing values (geom_errorbar).
## [1] "good"## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties
## obj.diff.bin delta.obj.subj n pval
## 1: 0.03125 NA 0 NA
## 2: 0.09375 0.1600 8 0.29 :(
## 3: 0.15625 0.0690 24 0.45 :(
## 4: 0.21875 0.0560 25 0.15 :(
## 5: 0.28125 0.0690 25 0.071 .
## 6: 0.34375 0.0560 25 0.089 .
## 7: 0.40625 0.0810 24 0.098 .
## 8: 0.46875 0.0940 24 0.031 *
## 9: 0.53125 0.0680 23 0.21 :(
## 10: 0.59375 0.0560 22 0.28 :(
## 11: 0.65625 -0.0062 22 1 :(
## 12: 0.71875 -0.0690 21 0.11 :(
## 13: 0.78125 -0.0650 15 0.081 .
## 14: 0.84375 NA 2 NA
## 15: 0.90625 NA 0 NA
## 16: 0.96875 NA 0 NA
## [1] "mean and sd of nb players per bin"
## nb pval
## 1: 8 0.29 :(
## 2: 24 0.45 :(
## 3: 25 0.15 :(
## 4: 25 0.071 .
## 5: 25 0.089 .
## 6: 24 0.098 .
## 7: 24 0.031 *
## 8: 23 0.21 :(
## 9: 22 0.28 :(
## 10: 22 1 :(
## 11: 21 0.11 :(
## 12: 15 0.081 .
## [1] 21.5
## [1] 5.07## Warning: Removed 4 rows containing missing values (geom_point).## Warning: Removed 4 rows containing missing values (geom_errorbar).
## [1] "medium"## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties
## obj.diff.bin delta.obj.subj n pval
## 1: 0.03125 NA 0 NA
## 2: 0.09375 NA 0 NA
## 3: 0.15625 0.290 5 0.28 :(
## 4: 0.21875 0.048 16 0.22 :(
## 5: 0.28125 0.120 23 0.07 .
## 6: 0.34375 0.069 24 0.26 :(
## 7: 0.40625 0.054 25 0.45 :(
## 8: 0.46875 0.031 25 0.25 :(
## 9: 0.53125 -0.028 25 0.63 :(
## 10: 0.59375 -0.069 22 0.23 :(
## 11: 0.65625 -0.130 23 0.019 *
## 12: 0.71875 -0.069 25 0.084 .
## 13: 0.78125 -0.120 25 0.013 *
## 14: 0.84375 -0.170 20 0.024 *
## 15: 0.90625 -0.170 6 0.14 :(
## 16: 0.96875 NA 0 NA
## [1] "mean and sd of nb players per bin"
## nb pval
## 1: 5 0.28 :(
## 2: 16 0.22 :(
## 3: 23 0.07 .
## 4: 24 0.26 :(
## 5: 25 0.45 :(
## 6: 25 0.25 :(
## 7: 25 0.63 :(
## 8: 22 0.23 :(
## 9: 23 0.019 *
## 10: 25 0.084 .
## 11: 25 0.013 *
## 12: 20 0.024 *
## 13: 6 0.14 :(
## [1] 20.3
## [1] 7.06## Warning: Removed 3 rows containing missing values (geom_point).## Warning: Removed 3 rows containing missing values (geom_errorbar).
## [1] "bad"## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable
## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties
## obj.diff.bin delta.obj.subj n pval
## 1: 0.03125 NA 0 NA
## 2: 0.09375 NA 0 NA
## 3: 0.15625 NA 0 NA
## 4: 0.21875 NA 0 NA
## 5: 0.28125 NA 0 NA
## 6: 0.34375 NA 1 NA
## 7: 0.40625 NA 1 NA
## 8: 0.46875 0.031 5 0.58 :(
## 9: 0.53125 NA 4 NA
## 10: 0.59375 -0.050 7 0.1 :(
## 11: 0.65625 -0.019 7 0.93 :(
## 12: 0.71875 -0.120 7 0.15 :(
## 13: 0.78125 -0.130 6 0.14 :(
## 14: 0.84375 -0.170 7 0.11 :(
## 15: 0.90625 -0.200 7 0.27 :(
## 16: 0.96875 -0.270 6 0.052 .
## [1] "mean and sd of nb players per bin"
## nb pval
## 1: 5 0.58 :(
## 2: 7 0.1 :(
## 3: 7 0.93 :(
## 4: 7 0.15 :(
## 5: 6 0.14 :(
## 6: 7 0.11 :(
## 7: 7 0.27 :(
## 8: 6 0.052 .
## [1] 6.5
## [1] 0.756## Warning: Removed 8 rows containing missing values (geom_point).## Warning: Removed 8 rows containing missing values (geom_errorbar).
Sensory task
## [1] "all"## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties
## obj.diff.bin delta.obj.subj n pval
## 1: 0.03125 0.0490 32 0.069 .
## 2: 0.09375 0.1200 48 0.0073 **
## 3: 0.15625 0.0940 51 0.015 *
## 4: 0.21875 0.0310 47 0.34 :(
## 5: 0.28125 0.0020 46 0.97 :(
## 6: 0.34375 -0.0440 41 0.67 :(
## 7: 0.40625 -0.0063 44 0.77 :(
## 8: 0.46875 -0.0190 42 0.63 :(
## 9: 0.53125 -0.1600 34 0.0078 **
## 10: 0.59375 -0.2400 37 0.00021 ***
## 11: 0.65625 -0.1600 40 0.00065 ***
## 12: 0.71875 -0.2200 46 1.8e-06 ***
## 13: 0.78125 -0.2700 42 3.2e-06 ***
## 14: 0.84375 -0.2400 46 3.4e-07 ***
## 15: 0.90625 -0.2200 53 4.6e-08 ***
## 16: 0.96875 -0.1300 55 3.7e-07 ***
## [1] "mean and sd of nb players per bin"
## nb pval
## 1: 32 0.069 .
## 2: 48 0.0073 **
## 3: 51 0.015 *
## 4: 47 0.34 :(
## 5: 46 0.97 :(
## 6: 41 0.67 :(
## 7: 44 0.77 :(
## 8: 42 0.63 :(
## 9: 34 0.0078 **
## 10: 37 0.00021 ***
## 11: 40 0.00065 ***
## 12: 46 1.8e-06 ***
## 13: 42 3.2e-06 ***
## 14: 46 3.4e-07 ***
## 15: 53 4.6e-08 ***
## 16: 55 3.7e-07 ***
## [1] 44
## [1] 6.4
## [1] "good"## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties
## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties
## obj.diff.bin delta.obj.subj n pval
## 1: 0.03125 0.1200 18 0.0087 **
## 2: 0.09375 0.0340 19 0.61 :(
## 3: 0.15625 0.0940 17 0.53 :(
## 4: 0.21875 -0.0190 13 0.89 :(
## 5: 0.28125 0.0021 13 0.83 :(
## 6: 0.34375 0.0062 13 0.83 :(
## 7: 0.40625 -0.1100 14 0.3 :(
## 8: 0.46875 -0.0690 16 0.26 :(
## 9: 0.53125 -0.1600 14 0.023 *
## 10: 0.59375 -0.3400 11 0.023 *
## 11: 0.65625 -0.2600 13 0.0085 **
## 12: 0.71875 -0.2900 16 0.00059 ***
## 13: 0.78125 -0.3600 13 0.0032 **
## 14: 0.84375 -0.2700 15 0.0018 **
## 15: 0.90625 -0.2300 18 0.0014 **
## 16: 0.96875 -0.1500 19 0.0064 **
## [1] "mean and sd of nb players per bin"
## nb pval
## 1: 18 0.0087 **
## 2: 19 0.61 :(
## 3: 17 0.53 :(
## 4: 13 0.89 :(
## 5: 13 0.83 :(
## 6: 13 0.83 :(
## 7: 14 0.3 :(
## 8: 16 0.26 :(
## 9: 14 0.023 *
## 10: 11 0.023 *
## 11: 13 0.0085 **
## 12: 16 0.00059 ***
## 13: 13 0.0032 **
## 14: 15 0.0018 **
## 15: 18 0.0014 **
## 16: 19 0.0064 **
## [1] 15.1
## [1] 2.5
## [1] "medium"## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties
## obj.diff.bin delta.obj.subj n pval
## 1: 0.03125 -0.031 14 0.39 :(
## 2: 0.09375 0.130 25 0.0036 **
## 3: 0.15625 0.094 25 0.15 :(
## 4: 0.21875 0.031 24 0.74 :(
## 5: 0.28125 -0.031 23 0.51 :(
## 6: 0.34375 -0.044 20 0.46 :(
## 7: 0.40625 -0.031 21 0.51 :(
## 8: 0.46875 0.019 20 0.78 :(
## 9: 0.53125 -0.160 16 0.13 :(
## 10: 0.59375 -0.170 20 0.034 *
## 11: 0.65625 -0.110 20 0.08 .
## 12: 0.71875 -0.220 21 0.0057 **
## 13: 0.78125 -0.180 20 0.0074 **
## 14: 0.84375 -0.270 23 0.00046 ***
## 15: 0.90625 -0.180 25 0.00025 ***
## 16: 0.96875 -0.069 26 0.0021 **
## [1] "mean and sd of nb players per bin"
## nb pval
## 1: 14 0.39 :(
## 2: 25 0.0036 **
## 3: 25 0.15 :(
## 4: 24 0.74 :(
## 5: 23 0.51 :(
## 6: 20 0.46 :(
## 7: 21 0.51 :(
## 8: 20 0.78 :(
## 9: 16 0.13 :(
## 10: 20 0.034 *
## 11: 20 0.08 .
## 12: 21 0.0057 **
## 13: 20 0.0074 **
## 14: 23 0.00046 ***
## 15: 25 0.00025 ***
## 16: 26 0.0021 **
## [1] 21.4
## [1] 3.33
## [1] "bad"## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable
## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties
## obj.diff.bin delta.obj.subj n pval
## 1: 0.03125 NA 0 NA
## 2: 0.09375 0.1600 4 0.58 :(
## 3: 0.15625 0.2000 9 0.043 *
## 4: 0.21875 0.0810 10 0.1 :(
## 5: 0.28125 0.0350 10 0.54 :(
## 6: 0.34375 0.0062 8 0.83 :(
## 7: 0.40625 0.0940 9 0.011 *
## 8: 0.46875 0.0310 6 0.83 :(
## 9: 0.53125 -0.0940 4 0.62 :(
## 10: 0.59375 -0.3400 6 0.031 *
## 11: 0.65625 -0.1600 7 0.26 :(
## 12: 0.71875 -0.2200 9 0.091 .
## 13: 0.78125 -0.2800 9 0.023 *
## 14: 0.84375 -0.1900 8 0.055 .
## 15: 0.90625 -0.2900 10 0.013 *
## 16: 0.96875 -0.2400 10 0.0059 **
## [1] "mean and sd of nb players per bin"
## nb pval
## 1: 4 0.58 :(
## 2: 9 0.043 *
## 3: 10 0.1 :(
## 4: 10 0.54 :(
## 5: 8 0.83 :(
## 6: 9 0.011 *
## 7: 6 0.83 :(
## 8: 4 0.62 :(
## 9: 6 0.031 *
## 10: 7 0.26 :(
## 11: 9 0.091 .
## 12: 9 0.023 *
## 13: 8 0.055 .
## 14: 10 0.013 *
## 15: 10 0.0059 **
## [1] 7.93
## [1] 2.09## Warning: Removed 1 rows containing missing values (geom_point).## Warning: Removed 1 rows containing missing values (geom_errorbar).
Logical task
## [1] "all"## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties
## obj.diff.bin delta.obj.subj n pval
## 1: 0.03125 0.1400 38 0.0033 **
## 2: 0.09375 0.1800 43 8.1e-06 ***
## 3: 0.15625 0.2000 48 3.1e-06 ***
## 4: 0.21875 0.1900 50 2e-06 ***
## 5: 0.28125 0.2200 49 6.1e-05 ***
## 6: 0.34375 0.1800 41 2.3e-05 ***
## 7: 0.40625 0.0940 47 0.011 *
## 8: 0.46875 0.0310 47 0.0053 **
## 9: 0.53125 -0.0310 45 0.087 .
## 10: 0.59375 0.0062 46 0.86 :(
## 11: 0.65625 -0.0810 42 0.15 :(
## 12: 0.71875 -0.1700 41 0.0011 **
## 13: 0.78125 -0.1600 53 7.2e-06 ***
## 14: 0.84375 -0.2400 52 1.4e-08 ***
## 15: 0.90625 -0.2600 42 1.2e-07 ***
## 16: 0.96875 -0.3900 29 2.6e-06 ***
## [1] "mean and sd of nb players per bin"
## nb pval
## 1: 38 0.0033 **
## 2: 43 8.1e-06 ***
## 3: 48 3.1e-06 ***
## 4: 50 2e-06 ***
## 5: 49 6.1e-05 ***
## 6: 41 2.3e-05 ***
## 7: 47 0.011 *
## 8: 47 0.0053 **
## 9: 45 0.087 .
## 10: 46 0.86 :(
## 11: 42 0.15 :(
## 12: 41 0.0011 **
## 13: 53 7.2e-06 ***
## 14: 52 1.4e-08 ***
## 15: 42 1.2e-07 ***
## 16: 29 2.6e-06 ***
## [1] 44.6
## [1] 5.93
## [1] "good"## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties
## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties
## obj.diff.bin delta.obj.subj n pval
## 1: 0.03125 0.079 28 0.054 .
## 2: 0.09375 0.140 28 0.00069 ***
## 3: 0.15625 0.130 27 0.003 **
## 4: 0.21875 0.160 25 0.0064 **
## 5: 0.28125 0.170 23 0.052 .
## 6: 0.34375 0.150 20 0.038 *
## 7: 0.40625 0.069 20 0.21 :(
## 8: 0.46875 0.031 24 0.097 .
## 9: 0.53125 -0.031 23 0.49 :(
## 10: 0.59375 -0.094 22 0.046 *
## 11: 0.65625 -0.081 21 0.26 :(
## 12: 0.71875 -0.130 19 0.055 .
## 13: 0.78125 -0.160 26 0.0022 **
## 14: 0.84375 -0.270 24 0.00011 ***
## 15: 0.90625 -0.310 15 0.0024 **
## 16: 0.96875 NA 1 NA
## [1] "mean and sd of nb players per bin"
## nb pval
## 1: 28 0.054 .
## 2: 28 0.00069 ***
## 3: 27 0.003 **
## 4: 25 0.0064 **
## 5: 23 0.052 .
## 6: 20 0.038 *
## 7: 20 0.21 :(
## 8: 24 0.097 .
## 9: 23 0.49 :(
## 10: 22 0.046 *
## 11: 21 0.26 :(
## 12: 19 0.055 .
## 13: 26 0.0022 **
## 14: 24 0.00011 ***
## 15: 15 0.0024 **
## [1] 23
## [1] 3.63## Warning: Removed 1 rows containing missing values (geom_point).## Warning: Removed 1 rows containing missing values (geom_errorbar).
## [1] "medium"## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties
## obj.diff.bin delta.obj.subj n pval
## 1: 0.03125 0.270 10 0.031 *
## 2: 0.09375 0.310 13 0.0019 **
## 3: 0.15625 0.340 16 0.0012 **
## 4: 0.21875 0.270 16 0.0019 **
## 5: 0.28125 0.220 15 0.0086 **
## 6: 0.34375 0.160 13 0.0038 **
## 7: 0.40625 0.094 14 0.017 *
## 8: 0.46875 0.031 13 0.12 :(
## 9: 0.53125 -0.031 12 0.16 :(
## 10: 0.59375 0.044 13 0.2 :(
## 11: 0.65625 -0.160 11 0.061 .
## 12: 0.71875 -0.170 14 0.14 :(
## 13: 0.78125 -0.250 15 0.0021 **
## 14: 0.84375 -0.260 15 0.00082 ***
## 15: 0.90625 -0.280 14 0.0015 **
## 16: 0.96875 -0.420 15 0.00072 ***
## [1] "mean and sd of nb players per bin"
## nb pval
## 1: 10 0.031 *
## 2: 13 0.0019 **
## 3: 16 0.0012 **
## 4: 16 0.0019 **
## 5: 15 0.0086 **
## 6: 13 0.0038 **
## 7: 14 0.017 *
## 8: 13 0.12 :(
## 9: 12 0.16 :(
## 10: 13 0.2 :(
## 11: 11 0.061 .
## 12: 14 0.14 :(
## 13: 15 0.0021 **
## 14: 15 0.00082 ***
## 15: 14 0.0015 **
## 16: 15 0.00072 ***
## [1] 13.7
## [1] 1.7
## [1] "bad"## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): requested conf.level not achievable## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact p-value with ties## Warning in wilcox.test.default(subj.diff, mu = obj.diff.bin.cur, conf.int =
## T): cannot compute exact confidence interval with ties
## obj.diff.bin delta.obj.subj n pval
## 1: 0.03125 NA 0 NA
## 2: 0.09375 NA 2 NA
## 3: 0.15625 0.340 5 0.28 :(
## 4: 0.21875 0.260 9 0.023 *
## 5: 0.28125 0.270 11 0.018 *
## 6: 0.34375 0.410 8 0.014 *
## 7: 0.40625 0.094 13 0.44 :(
## 8: 0.46875 0.100 10 0.083 .
## 9: 0.53125 -0.031 10 0.21 :(
## 10: 0.59375 0.120 11 0.12 :(
## 11: 0.65625 0.069 10 0.53 :(
## 12: 0.71875 -0.210 8 0.02 *
## 13: 0.78125 -0.062 12 0.25 :(
## 14: 0.84375 -0.140 13 0.014 *
## 15: 0.90625 -0.240 13 0.004 **
## 16: 0.96875 -0.370 13 0.0016 **
## [1] "mean and sd of nb players per bin"
## nb pval
## 1: 5 0.28 :(
## 2: 9 0.023 *
## 3: 11 0.018 *
## 4: 8 0.014 *
## 5: 13 0.44 :(
## 6: 10 0.083 .
## 7: 10 0.21 :(
## 8: 11 0.12 :(
## 9: 10 0.53 :(
## 10: 8 0.02 *
## 11: 12 0.25 :(
## 12: 13 0.014 *
## 13: 13 0.004 **
## 14: 13 0.0016 **
## [1] 10.4
## [1] 2.38## Warning: Removed 2 rows containing missing values (geom_point).## Warning: Removed 2 rows containing missing values (geom_errorbar).